Computational model investigates the evolution of colonic crypts during Lynch syndrome carcinogenesis - Haupt, Saskia; Gleim, Nils; Ahadova, Aysel; Bläker, Hendrik; von Knebel Doeberitz, Magnus; Kloor, Matthias; Heuveline, Vincent (2020)

Introducing Biomedisa as an open-source online platform for biomedical image segmentation - Lösel, Philipp; van de Kamp, Thomas; Jayme, Alejandra; Ershov, Alexey; Faragó, Tomáš; Pichler, Olaf; Tan Jerome, Nicholas; Aadepu, Narendar; Bremer, Sabine; Chilingaryan, Suren A.; Heethoff, Michael; Kopmann, Andreas; et al. (Nature Communications, 2020)

Biomechanics applied to incisional hernia repair – Considering the critical and the gained resistance towards impacts related to pressure - Kallinowski, F.; Ludwig, Y.; Löffler, T.; Vollmer, M.; Lösel, Philipp; Voß, S.; Görich, J.; Heuveline, Vincent; Nessel, R. (Clinical Biomechanics, 2021)

Characterization Simulation of a Bulk MOSFET in Steady-State with SIPG Method - Zhu, Jun-Yan; Song, Chen; Heuveline, Vincent; Li, Bo; Li, Bin-Hong; Han, Zheng-Sheng; Liu, Xin-Yu (2020 IEEE 15th International Conference on Solid-State & Integrated Circuit Technology (ICSICT), 2020)

A Simple Model for Portable and Fast Prediction of Execution Time and Power Consumption of GPU Kernels - Braun, Lorenz; Nikas, Sotirios; Song, Chen; Heuveline, Vincent; Fröning, Holger (ACM Transactions on Architecture and Code Optimization, 2021)

Computational ligand superimposition and analysis of protein-ligand interaction fingerprints - Ormersbach, Fabian (2020)

Computational modeling of SERCA interactions with S100A1ct and DWORF fingerprints - Jarosch, Lukas (2020)

Computational approaches to drug design against the folate & biopterin pathways of parasites causing neglected tropical diseases - Pöhner, Ina A. (2020)

Molecular mechanisms of AMPAR modulation by auxiliary subunits - Dohrke, Jan-Niklas (2021)

Putative second hit rare genetic variants in families with seemingly GBA-associated Parkinson’s disease - Aslam, Muhammad; Kandasamy, Nirosiya; Ullah, Anwar; Paramasivam, Nagarajan; Öztürk, Mehmet Ali; Naureen, Saima; Arshad, Abida; Badshah, Mazhar; Khan, Kafaitullah; Wajid, Muhammad; Abbasi, Rashda; Ilyas, Muhammad; et al. (npj Genomic Medicine, 2021)
Abstract

Fine-Tuning of Sequence Specificity by Near Attack Conformations in Enzyme-Catalyzed Peptide Hydrolysis - Sadiq, Kashif (Catalysts, 2020)

Towards standardization guidelines for in silico approaches in personalized medicine - Brunak, Søren; Bjerre Collin, Catherine; Eva Ó Cathaoir, Katharina; Golebiewski, Martin; Kirschner, Marc; Kockum, Ingrid; Moser, Heike; Waltemath, Dagmar (Journal of Integrative Bioinformatics, 2020)
Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.

COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms - Ostaszewski, Marek; Niarakis, Anna; Mazein, Alexander; Kuperstein, Inna; Phair, Robert; Orta-Resendiz, Aurelio; Singh, Vidisha; Aghamiri, Sara Sadat; Acencio, Marcio Luis; Glaab, Enrico; Ruepp, Andreas; Fobo, Gisela; et al. (2020)
We hereby describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied to the contents of the COVID-19 Disease Map for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases.

FAST, ADAPTED, CURATED FAIR DATA FOR COVID-19 RESEARCH - Rey, Maja; Weidemann, Andreas; Wittig, Ulrike; Dudas, Dorotea; Ghosh, Sucheta; Golebiewski, Martin; Hu, Xiaoming; Müller, Wolfgang (2021)
Research projects such as the international COVID-19 Disease Map initiative and the German COVID-19 study hub of NFDI are supported by de.NBI-SysBio tools and services in organizing and sharing research data ’FAIRly‘. This is done via the data management platform FAIRDOMHub/SEEK which is quickly adapted to the users' needs. COVID-19 related literature is manually curated and used for basic research about the curation process of SABIO-RK to provide the research community with high quality kinetics data.

Specifications of standards in systems and synthetic biology: status and developments in 2020 - Schreiber, Falk; Sommer, Björn; Czauderna, Tobias; Golebiewski, Martin; Gorochowski, Thomas E.; Hucka, Michael; Keating, Sarah M.; König, Matthias; Myers, Chris; Nickerson, David; Waltemath, Dagmar (Journal of Integrative Bioinformatics, 2020)
This special issue of the Journal of Integrative Bioinformatics presents papers related to the 10th COMBINE meeting together with the annual update of COMBINE standards in systems and synthetic biology.

A function of profilin in force generation during malaria parasite motility that is independent of actin binding - Moreau, Catherine A.; Quadt, Katharina A.; Piirainen, Henni; Kumar, Hirdesh; Bhargav, Saligram P.; Strauss, Léanne; Tolia, Niraj H.; Wade, Rebecca C.; Spatz, Joachim P.; Kursula, Inari; Frischknecht, Friedrich (Journal of Cell Science, 2021)
During transmission of malaria-causing parasites from mosquito to mammal, Plasmodium sporozoites migrate at high speed within the skin to access the bloodstream and infect the liver. This unusual gliding motility is based on retrograde flow of membrane proteins and highly dynamic actin filaments that provide short tracks for a myosin motor. Using laser tweezers and parasite mutants, we previously suggested that actin filaments form macromolecular complexes with plasma membrane-spanning adhesins to generate force during migration. Mutations in the actin-binding region of profilin, a near ubiquitous actin-binding protein, revealed that loss of actin binding also correlates with loss of force production and motility. Here, we show that different mutations in profilin, that do not affect actin binding in vitro, still generate lower force during Plasmodium sporozoite migration. Lower force generation inversely correlates with increased retrograde flow suggesting that, like in mammalian cells, the slow down of flow to generate force is the key underlying principle governing Plasmodium gliding motility.

Structure-kinetic relationship reveals the mechanism of selectivity of FAK inhibitors over PYK2 - Berger, Benedict-Tilman; Amaral, Marta; Kokh, Daria; Nunes Alves, Ariane; Musil, Djordje; Heinrich, Timo; Schröder, Martin; Neil, Rebecca; Wang, Jing; Navratilova, Iva; Bomke, Joerg; Elkins, Jonathan M.; et al. (Cell Chemical Biology, 2021)

The real spectrum compactification of character varieties: characterizations and applications
We announce results on a compactification of general character varieties that has good topological properties and give various interpretations of its ideal points. We relate this to the Weyl chamber length compactification and apply our results to the theory of maximal and Hitchin representations.

Renormalizing an infinite rational IET - Patrick Hooper, W.; Rafi, Kasra; Randecker, Anja (Discrete & Continuous Dynamical Systems - A, 2020)
We study an interval exchange transformation of [0,1] formed by cutting the interval at the points 1/n and reversing the order of the intervals. We find that the transformation is periodic away from a Cantor set of Hausdorff dimension zero. On the Cantor set, the dynamics are nearly conjugate to the 2-adic odometer.

Topological mixing of Weyl chamber flows - DANG, NGUYEN-THI; GLORIEUX, OLIVIER (Ergodic Theory and Dynamical Systems, 2020)
In this paper we study topological properties of the right action by translation of the Weyl chamber flow on the space of Weyl chambers. We obtain a necessary and sufficient condition for topological mixing.

Signature cocycles on the mapping class group and symplectic groups - Benson, Dave; Campagnolo, Caterina; Ranicki, Andrew; Rovi, Carmen (Journal of Pure and Applied Algebra, 2020)
Werner Meyer constructed a cocycle in H^2(Sp_2(g,Z); Z) which computes the signature of a closed oriented surface bundle over a surface. By studying properties of this cocycle, he also showed that the signature of such a surface bundle is a multiple of 4. In this paper, we study signature cocycles both from the geometric and algebraic points of view. We present geometric constructions which are relevant to the signature cocycle and provide an alternative to Meyer's decomposition of a surface bundle. Furthermore, we discuss the precise relation between the Meyer and Wall-Maslov index. The main theorem of the paper, Theorem 6.6, provides the necessary group cohomology results to analyze the signature of a surface bundle modulo any integer N. Using these results, we are able to give a complete answer for N=2,4 and 8, and based on a theorem of Deligne, we show that this is the best we can hope for using this method.

Open Problems in the Topology of Manifolds - Bowden, Jonathan; Crowley, Diarmuid; Davis, Jim; Friedl, Stefan; Rovi, Carmen; Tillmann, Stephan (2019-20 MATRIX Annals, 2021)

Flows on the $$PGL(V)$$-Hitchin Component - Sun, Zhe; Wienhard, Anna; Zhang, Tengren (Geometric and Functional Analysis, 2020)
In this article we define new flows on the Hitchin components for PSL(n,R). Special examples of these flows are associated to simple closed curves on the surface and give generalized twist flows. Other examples, so called eruption flows, are associated to pair of pants in S and capture new phenomena which are not present in the case when n = 2. We determine a global coordinate system on the Hitchin component. Using the computation of the Goldman symplectic form on the Hitchin component, that is developed by two of the authors in a companion paper to this article (Sun and Zhang in The Goldman symplectic form on the PGL(V)-Hitchin component, 2017. arXiv:1709.03589), this gives a global Darboux coordinate system on the Hitchin component.

3D hydrodynamic simulations of C ingestion into a convective O shell - Andrássy, Róbert; Herwig, F; Woodward, P; Ritter, C (Monthly Notices of the Royal Astronomical Society, 2020)

3D1D hydro-nucleosynthesis simulations. I. Advective-reactive post-processing method and its application to H ingestion into He-shell flash convection in rapidly accreting white dwarfs - Stephens, David; Herwig, Falk; Woodward, Paul; Denissenkov, Pavel; Andrássy, Róbert; Mao, Huaqing (Monthly Notices of the Royal Astronomical Society, 2021)

Line-FRAP, A Versatile Method to Measure Diffusion Rates In Vitro and In Vivo - Dey, Debabrata; Marciano, Shir; Nunes Alves, Ariane; Kiss, Vladimir; Wade, Rebecca C.; Schreiber, Gideon (Journal of Molecular Biology, 2021)

Unveiling the rarest morphologies of the LOFAR Two-metre Sky Survey radio source population with self-organised maps - Mostert, Rafaël I. J.; Duncan, Kenneth J.; Röttgering, Huub J. A.; Polsterer, Kai; Best, Philip N.; Brienza, Marisa; Brüggen, Marcus; Hardcastle, Martin J.; Jurlin, Nika; Mingo, Beatriz; Morganti, Raffaella; Shimwell, Tim; et al. (Astronomy & Astrophysics, 2021)

Birds of a Feather Session on Machine Learning in Astronomy - Polsterer, Kai (Astronomical Data Analysis Software and Systems XXVII, 2020)

Sensing and sensitivity: Computational chemistry of graphene‐based sensors - Piras, Anna; Ehlert, Christopher; Gryn'ova, Ganna (WIREs Computational Molecular Science, 2021)
Highly efficient, tunable, biocompatible, and environmentally friendly electrochemical sensors featuring graphene‐based materials pose a formidable challenge for computational chemistry. In silico rationalization, optimization and, ultimately, prediction of their performance requires exploring a vast structural space of potential surface‐analyte complexes, further complicated by the presence of various defects and functionalities within the infinite graphene lattice. This immense number of systems and their periodic nature greatly limit the choice of computational tools applicable at a reasonable cost. An alternative approach using finite nanoflake models opens the doors to many more advanced and accurate electronic structure methods, while sacrificing the realism of representation. Locating the surface‐analyte complex is followed by an in‐depth in silico analysis of its energetic and electronic properties using, for example, energy decomposition schemes, as well as simulation of the signal, for example, a zero‐bias transmission spectra or a current–voltage curve, by means of the nonequilibrium Green's function method. These and other properties are examined in the context of a sensor's selectivity, sensitivity, and limit of detection with an aim to establish design principles for future devices. Herein, we analyze the advantages and limitations of diverse computational chemistry methods used at each of these steps in simulating graphene‐based electrochemical sensors. We present outstanding challenges toward predictive models and sketch possible solutions involving such contemporary techniques as multiscale simulations and high‐throughput screening.

PSIXAS : A Psi4 plugin for efficient simulations of X‐ray absorption spectra based on the transition‐potential and Δ‐Kohn–Sham method - Ehlert, Christopher; Klamroth, Tillmann (Journal of Computational Chemistry, 2020)
Near edge X‐ray absorption fine structure (NEXAFS) spectra and their pump‐probe extension (PP‐NEXAFS) offer insights into valence‐ and core‐excited states. We present PSIXAS, a recent implementation for simulating NEXAFS and PP‐NEXAFS spectra by means of the transition‐potential and the Δ‐Kohn–Sham method. The approach is implemented in form of a software plugin for the Psi4 code, which provides access to a wide selection of basis sets as well as density functionals. We briefly outline the theoretical foundation and the key aspects of the plugin. Then, we use the plugin to simulate PP‐NEXAFS spectra of thymine, a system already investigated by others and us. It is found that larger, extended basis sets are needed to obtain more accurate absolute resonance positions. We further demonstrate that, in contrast to ordinary NEXAFS simulations, where the choice of the density functional plays a minor role for the shape of the spectrum, for PP‐NEXAFS simulations the choice of the density functional is important. Especially hybrid functionals (which could not be used straightforwardly before to simulate PP‐NEXAFS spectra) and their amount of “Hartree‐Fock like” exact exchange affects relative resonance positions in the spectrum.

From Supernova to Supernova Remnant: Comparison of Thermonuclear Explosion Models - Ferrand, Gilles; Warren, Donald C.; Ono, Masaomi; Nagataki, Shigehiro; Röpke, Friedrich; Seitenzahl, Ivo R.; Lach, Florian; Iwasaki, Hiroyoshi; Sato, Toshiki (\apj, 2021)

Nucleosynthesis imprints from different Type Ia supernova explosion scenarios and implications for galactic chemical evolution - Lach, Florian; Röpke, Friedrich; Seitenzahl, I. R.; Coté, B.; Gronow, Sabrina; Ruiter, A. J. (\aap, 2020)

Common-envelope evolution with an asymptotic giant branch star - Sand, Christian; Ohlmann, Sebastian T.; Schneider, Fabian; Pakmor, Rüdiger; Röpke, Friedrich (\aap, 2020)

VizieR Online Data Catalog: OB stars TESS phot. & high-resolution spectroscopy (Bowman+, 2020) - Bowman, D. M.; Burssens, S.; Simon-Diaz, S.; Edelmann, P. V. F.; Rogers, T. M.; Horst, Leonhard; Röpke, Friedrich; Aerts, C. (VizieR Online Data Catalog, 2020)

Formation of sdB-stars via common envelope ejection by substellar companions - Kramer, Manuel; Schneider, Fabian; Ohlmann, S. T.; Geier, S.; Schaffenroth, V.; Pakmor, R.; Röpke, Friedrich (\aap, 2020)

Long-term evolution of a magnetic massive merger product - Schneider, Fabian; Ohlmann, S. T.; Podsiadlowski, Ph; Röpke, Friedrich; Balbus, S. A.; Pakmor, R. (\mnras, 2020)

White dwarf deflagrations for Type Iax supernovae: polarisation signatures from the explosion and companion interaction - Bulla, M.; Liu, Z. -W.; Röpke, Friedrich; Sim, S. A.; Fink, M.; Kromer, M.; Pakmor, R.; Seitenzahl, I. R. (\aap, 2020)

Monte Carlo radiative transfer for the nebular phase of Type Ia supernovae - Shingles, L. J.; Sim, S. A.; Kromer, M.; Maguire, K.; Bulla, M.; Collins, C.; Ballance, C. P.; Michel, A. S.; Ramsbottom, C. A.; Röpke, Friedrich; Seitenzahl, I. R.; Tyndall, N. B. (\mnras, 2020)

Late-phase radiative transfer of Type Ia supernovae - Shingles, L.; Sim, S. A.; Kromer, M.; Maguire, K.; Bulla, M.; Collins, C.; Ballance, C. P.; Michel, A. S.; Ramsbottom, C. A.; Röpke, Friedrich; Seitenzahl, I. R.; Tyndall, N. B. (2019)

From the (thermonuclear) supernova to the supernova remnant - Ferrand, G.; Warren, D.; Ono, M.; Nagataki, S.; Röpke, Friedrich; Seitenzahl, I. (2019)

Type Iax Supernovae from Deflagrations of Chandrasekhar Mass White Dwarfs - Lach, Florian; Röpke, Friedrich; Kromer, M. (2019)

A sub-Chandrasekhar mass white dwarf as possible progenitor for a thermonuclear explosion - Gronow, Sabrina; Röpke, Friedrich (2019)

VizieR Online Data Catalog: From optical to infrared photometry of SN 2013dy (Pan+, 2015) - Pan, Y. -C.; Foley, R. J.; Kromer, M.; Fox, O. D.; Zheng, W.; Challis, P.; Clubb, K. I.; Filippenko, A. V.; Folatelli, G.; Graham, M. L.; Hillebrandt, W.; Kirshner, R. P.; et al. (VizieR Online Data Catalog, 2017)

Simulating the observed diversity of Type Ia supernovae . Introducing a model data base - Kromer, M.; Ohlmann, S.; Röpke, Friedrich (\memsai, 2017)

Pre-outburst HST imaging of Gaia16cfr - Kilpatrick, C. D.; Foley, R. J.; Pan, Y. -C.; Brown, P. J.; Filippenko, A. V.; Kasen, D.; Folatelli, G.; Fox, O. D.; Hillenbrandt, W.; Tauenberger, S.; Hsiao, E.; Kirshner, R. P.; et al. (The Astronomer’s Telegram, 2017)

Understanding the Progenitor Systems, Explosion Mechanisms, and Cosmological Utility of Type Ia Supernovae - Foley, Ryan; Brown, Peter J.; Challis, Peter; Filippenko, Alex V.; Folatelli, Gaston; Fox, Ori Dosovitz; Hillebrandt, Wolfgang; Hsiao, Eric; Kasen, Daniel; Kirshner, Robert P.; Kromer, Markus; Marion, G. H.; et al. (2016)

Calibrating core overshooting parameters with two-dimensional hydrodynamical simulations - Higl, J.; Müller, E.; Weiss, A. (Astronomy & Astrophysics, 2021)

An analysis of the TZ Fornacis binary system - Higl, J.; Siess, L.; Weiss, A.; Ritter, H. (Astronomy & Astrophysics, 2018)

Testing stellar evolution models with detached eclipsing binaries - Higl, J.; Weiss, A. (Astronomy & Astrophysics, 2017)

A Protocol to Use Comparative Binding Energy Analysis to Estimate Drug-Target Residence Time - Ganotra, Gaurav K.; Nunes Alves, Ariane; Wade, Rebecca C. (Protein-Ligand Interactions and Drug Design, 2021)

A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics - Gossen, Jonas; Albani, Simone; Hanke, Anton; Joseph, Benjamin P.; Bergh, Cathrine; Kuzikov, Maria; Costanzi, Elisa; Manelfi, Candida; Storici, Paola; Gribbon, Philip; Beccari, Andrea R.; Talarico, Carmine; et al. (ACS Pharmacology & Translational Science, 2021)

Mechanical characterization and induced crystallization in nanocomposites of thermoplastics and carbon nanotubes - Cruz-Chú, Eduardo R.; Villegas-Rodriguez, Gonzalo; Jäger, Tobias; Valentini, Luca; Pugno, Nicola; Gkagkas, Konstantinos; Gräter, Frauke (npj Computational Materials, 2020)
Nanocomposites built from polymers and carbon nanotubes (CNTs) are a promising class of materials. Computer modeling can provide nanoscale views of the polymer-CNT interface, which are much needed to foster the manufacturing and development of such materials. However, setting up periodic nanocomposite models is a challenging task. Here we propose a computational workflow based on Molecular Dynamics simulations. We demonstrate its capabilities and showcase its applications, focusing on two existing nanocomposite materials: polystyrene (PS) with CNT and polyether ether ketone with CNT. The models provide insights into the polymer crystallization inside CNTs. Furthermore, the PS+CNT nanocomposite models are mechanically tested and able to predict an enhancement in Young's modulus due to the addition of highly dispersed CNTs. We accompany those results with experimental tests and provide a prediction model based on Dynamic Quantized Fracture Mechanics theory. Our study proposes representative simulations of polymer-CNT nanocomposites as promising tools to guide the rational design of this class of materials.

Structural basis of Focal Adhesion Kinase activation on lipid membranes. - Acebron, I.; Righetto, R. D.; Schoenherr, C.; de Buhr, S.; Redondo, P.; Culley, J.; Rodriguez, C. F.; Daday, C.; Biyani, N.; Llorca, O.; Byron, A.; Chami, M.; et al. (EMBO J, 2020)
Focal adhesion kinase (FAK) is a key component of the membrane proximal signaling layer in focal adhesion complexes, regulating important cellular processes, including cell migration, proliferation, and survival. In the cytosol, FAK adopts an autoinhibited state but is activated upon recruitment into focal adhesions, yet how this occurs or what induces structural changes is unknown. Here, we employ cryo-electron microscopy to reveal how FAK associates with lipid membranes and how membrane interactions unlock FAK autoinhibition to promote activation. Intriguingly, initial binding of FAK to the membrane causes steric clashes that release the kinase domain from autoinhibition, allowing it to undergo a large conformational change and interact itself with the membrane in an orientation that places the active site toward the membrane. In this conformation, the autophosphorylation site is exposed and multiple interfaces align to promote FAK oligomerization on the membrane. We show that interfaces responsible for initial dimerization and membrane attachment are essential for FAK autophosphorylation and resulting cellular activity including cancer cell invasion, while stable FAK oligomerization appears to be needed for optimal cancer cell proliferation in an anchorage-independent manner. Together, our data provide structural details of a key membrane bound state of FAK that is primed for efficient autophosphorylation and activation, hence revealing the critical event in integrin mediated FAK activation and signaling at focal adhesions.
Keywords: Animals; Avian Proteins/*chemistry/metabolism; Chickens; Enzyme Activation; Focal Adhesion Protein-Tyrosine Kinases/*chemistry/metabolism; HEK293 Cells; Humans; Membranes/*chemistry/enzymology; *Protein Multimerization; Structure-Activity Relationship

ATP allosterically stabilizes integrin-linked kinase for efficient force generation - Martin, Isabel; Nava, Michele; Wickström, Sara; Gräter, Frauke (Proceedings of the National Academy of Sciences, 2022)
Focal adhesions link the actomyosin cytoskeleton to the extracellular matrix regulating cell adhesion, shape, and migration. Adhesions are dynamically assembled and disassembled in response to extrinsic and intrinsic forces, but how the essential adhesion component intergrin-linked kinase (ILK) dynamically responds to mechanical force and what role ATP bound to this pseudokinase plays remains elusive. Here, we apply force-probe molecular dynamics simulations of human ILK:α-parvin coupled to traction force microscopy to explore ILK mechanotransducing functions. We identify two key saltbridge-forming arginines within the allosteric, ATP-dependent force-propagation network of ILK. Disrupting this network by mutation impedes parvin binding, focal adhesion stabilization, force generation, and thus migration. Under tension, ATP shifts the balance from rupture of the complex to protein unfolding, indicating that ATP increases the force threshold required for focal adhesion disassembly. Our study proposes a new role of ATP as an obligatory binding partner for structural and mechanical integrity of the pseudokinase ILK, ensuring efficient cellular force generation and migration.

Comparison of outlier detection methods on astronomical image data - Doorenbos, Lars; Cavuoti, Stefano; Brescia, Massimo; D'Isanto, Antonio; Longo, Giuseppe (2020)
Among the many challenges posed by the huge data volumes produced by the new generation of astronomical instruments there is also the search for rare and peculiar objects. Unsupervised outlier detection algorithms may provide a viable solution. In this work we compare the performances of six methods: the Local Outlier Factor, Isolation Forest, k-means clustering, a measure of novelty, and both a normal and a convolutional autoencoder. These methods were applied to data extracted from SDSS stripe 82. After discussing the sensitivity of each method to its own set of hyperparameters, we combine the results from each method to rank the objects and produce a final list of outliers.

The Law of Attraction: Relating Computed Energetics of Physisorption with Performance of Graphene-Based Sensors for Nitroaromatic Contaminants - Piras, Anna; Gryn'ova, Ganna (2021)
The ability to detect persistent nitroaromatic contaminants, e.g. DNT and TNT, with high sensitivity and selectivity is central to environmental science and medicinal diagnostics. Graphene-based materials rise to this challenge, offering supreme performance, biocompatibility, and low toxicity at a reasonable cost. In the first step of the electrochemical sensing process, these substrates establish non-covalent interactions with the analytes, which we show to be indicative of their respective detection limits. Employing a combination of semiempirical tight binding quantum chemistry, meta- dynamics, density functional theory, and symmetry-adapted perturbation theory in conjunction with curated data from experimental literature, we investigate the physisorption of DNT and TNT on a series of functionalised graphene derivatives. In agreement with experimental observations, systems with greater planarity and positively charged substrates afford stronger non-covalent interactions than their highly oxidised distorted counterparts. Despite the highly polar nature of the investigated species, their non-covalent interactions are largely driven by dispersion forces. To harness these design principles, we considered a series of boron and nitrogen (co)doped two-dimensional materials. One of these systems featuring a chain of B–N–C units was found to adsorb nitroaromatic molecules stronger than the pristine graphene itself. These findings form the basis for the design principles of sensing materials and illustrate the utility of relatively low cost in silico procedures for testing the viability of designed graphene-based sensors for a plethora of analytes.

The Spectacular Ultraviolet Flash from the Peculiar Type Ia Supernova 2019yvq - Miller, A. A.; Magee, M. R.; Polin, A.; Maguire, K.; Zimmerman, E.; Yao, Y.; Sollerman, J.; Schulze, S.; Perley, D. A.; Kromer, M.; Dhawan, S.; Bulla, M.; et al. (\apj, 2020)

HOLISMOKES. I. Highly Optimised Lensing Investigations of Supernovae, Microlensing Objects, and Kinematics of Ellipticals and Spirals - Suyu, S. H.; Huber, S.; Cañameras, R.; Kromer, M.; Schuldt, S.; Taubenberger, S.; Yıldırım, A.; Bonvin, V.; Chan, J. H. H.; Courbin, F.; Nöbauer, U.; Sim, S. A.; et al. (\aap, 2020)

Word-Level Alignment of Paper Documents with their Electronic Full-Text Counterparts - Müller, Mark-Christoph; Ghosh, Sucheta; Wittig, Ulrike; Rey, Maja (2021)

Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach - López, Federico; Pozzetti, Beatrice; Trettel, Steve; Strube, Michael; Wienhard, Anna (2021)

Simulation of the Positive Inotropic Peptide S100A1ct in Aqueous Environment by Gaussian Accelerated Molecular Dynamics - Glaser, Manuel; Bruce, Neil J.; Han, Sungho Bosco; Wade, Rebecca C. (The Journal of Physical Chemistry B, 2021)

Ligand unbinding mechanisms and kinetics for T4 lysozyme mutants from τRAMD simulations - Nunes Alves, Ariane; Kokh, Daria; Wade, Rebecca C. (Current Research in Structural Biology, 2021)

Systematics of prompt black-hole formation in neutron star mergers - Bauswein, Andreas; Blacker, Sebastian; Lioutas, Georgios; Soultanis, Theodoros; Vijayan, Vimal; Stergioulas, Nikolaos (Physical Review D, 2021)

Bio-entity recognition for SABIO-RK database - Ghosh, Sucheta; Rey, Maja; Wittig, Ulrike; Müller, Wolfgang (F1000Research, 2019)

A Bittersweet Computational Journey among Glycosaminoglycans - Paiardi, Giulia; Milanesi, Maria; Wade, Rebecca C.; D’Ursi, Pasqualina; Rusnati, Marco (Biomolecules, 2021)

Brownian Dynamics Simulations of Proteins in the Presence of Surfaces: Long-Range Electrostatics and Mean-Field Hydrodynamics - Reinhardt, Martin; Bruce, Neil J.; Kokh, Daria; Wade, Rebecca C. (Journal of Chemical Theory and Computation, 2021)

Prediction of the Drug–Target Binding Kinetics for Flexible Proteins by Comparative Binding Energy Analysis - Nunes Alves, Ariane; Ormersbach, Fabian; Wade, Rebecca C. (Journal of Chemical Information and Modeling, 2021)

DNA sequence-dependent positioning of the linker histone in a nucleosome: A single-pair FRET study - De, Madhura; Öztürk, Mehmet Ali; Isbaner, Sebastian; Tóth, Katalin; Wade, Rebecca C. (Biophysical Journal, 2021)

Facilitating Study and Item Level Browsing for Clinical and Epidemiological COVID-19 Studies. - Schmidt, C. O.; Darms, J.; Shutsko, A.; Lobe, M.; Nagrani, R.; Seifert, B.; Lindstadt, B.; Golebiewski, M.; Koleva, S.; Bender, T.; Bauer, C. R.; Sax, U.; et al. (Stud Health Technol Inform, 2021)
COVID-19 poses a major challenge to individuals and societies around the world. Yet, it is difficult to obtain a good overview of studies across different medical fields of research such as clinical trials, epidemiology, and public health. Here, we describe a consensus metadata model to facilitate structured searches of COVID-19 studies and resources along with its implementation in three linked complementary web-based platforms. A relational database serves as central study metadata hub that secures compatibilities with common trials registries (e.g. ICTRP and standards like HL7 FHIR, CDISC ODM, and DataCite). The Central Search Hub was developed as a single-page application, the other two components with additional frontends are based on the SEEK platform and MICA, respectively. These platforms have different features concerning cohort browsing, item browsing, and access to documents and other study resources to meet divergent user needs. By this we want to promote transparent and harmonized COVID-19 research.
Keywords: *COVID-19; Epidemiologic Studies; Humans; Metadata; Registries; SARS-CoV-2

COVID-19-Forschungsdaten leichter zugänglich machen – Aufbau einer bundesweiten Informationsinfrastruktur - Schmidt, Carsten Oliver; Fluck, Juliane; Golebiewski, Martin; Grabenhenrich, Linus; Hahn, Horst; Kirsten, Toralf; Klammt, Sebastian; Löbe, Matthias; Sax, Ulrich; Thun, Sylvia; Pigeot, Iris; Ahrens, Wolfgang; et al. (Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, 2021)
Public-Health-Forschung, epidemiologische und klinische Studien sind erforderlich, um die COVID-19-Pandemie besser zu verstehen und geeignete Maßnahmen zu ergreifen. Daher wurden auch in Deutschland zahlreiche Forschungsprojekte initiiert. Zum heutigen Zeitpunkt ist es ob der Fülle an Informationen jedoch kaum noch möglich, einen Überblick über die vielfältigen Forschungsaktivitäten und deren Ergebnisse zu erhalten. Im Rahmen der Initiative „Nationale Forschungsdateninfrastruktur für personenbezogene Gesundheitsdaten“ (NFDI4Health) schafft die „Task Force COVID-19“ einen leichteren Zugang zu SARS-CoV-2- und COVID-19-bezogenen klinischen, epidemiologischen und Public-Health-Forschungsdaten. Dabei werden die sogenannten FAIR-Prinzipien (Findable, Accessible, Interoperable, Reusable) berücksichtigt, die eine schnellere Kommunikation von Ergebnissen befördern sollen. Zu den wesentlichen Arbeitsinhalten der Taskforce gehören die Erstellung eines Studienportals mit Metadaten, Erhebungsinstrumenten, Studiendokumenten, Studienergebnissen und Veröffentlichungen sowie einer Suchmaschine für Preprint-Publikationen. Weitere Inhalte sind ein Konzept zur Verknüpfung von Forschungs- und Routinedaten, Services zum verbesserten Umgang mit Bilddaten und die Anwendung standardisierter Analyseroutinen für harmonisierte Qualitätsbewertungen. Die im Aufbau befindliche Infrastruktur erleichtert die Auffindbarkeit von und den Umgang mit deutscher COVID-19-Forschung. Die im Rahmen der NFDI4Health Task Force COVID-19 begonnenen Entwicklungen sind für weitere Forschungsthemen nachnutzbar, da die adressierten Herausforderungen generisch für die Auffindbarkeit von und den Umgang mit Forschungsdaten sind.

Phylourny: Predicting the Knock-out-phase of Tournaments via Phylogenetic Methods by example of the UEFA EURO 2020 - Bettisworth, Ben; Stamatakis, Alexandros (2021)

Contact Map Fingerprints of Protein–Ligand Unbinding Trajectories Reveal Mechanisms Determining Residence Times Computed from Scaled Molecular Dynamics - Bianciotto, Marc; Gkeka, Paraskevi; Kokh, Daria B.; Wade, Rebecca C.; Minoux, Hervé (Journal of Chemical Theory and Computation, 2021)

G Protein-Coupled Receptor–Ligand Dissociation Rates and Mechanisms from τRAMD Simulations - Kokh, Daria B.; Wade, Rebecca C. (Journal of Chemical Theory and Computation, 2021)

Dioxygen Activation and Pyrrole α‐Cleavage with Calix[4]pyrrolato Aluminates: Enzyme Model by Structural Constraint - Sigmund, Lukas Maximilian; Ehlert, Christopher; Enders, Markus; Graf, Jürgen; Gryn'ova, Ganna; Greb, Lutz (Angewandte Chemie International Edition, 2021)
The present work describes the reaction of triplet dioxygen with the porphyrinogenic calix[4]pyrrolato aluminates to alkylperoxido aluminates in high selectivity. Multiconfigurational quantum chemical computations disclose the mechanism for this spin-forbidden process. Despite a negligible spin–orbit coupling constant, the intersystem crossing (ISC) is facilitated by singlet and triplet state degeneracy and spin–vibronic coupling. The formed peroxides are stable toward external substrates but undergo an unprecedented oxidative pyrrole α-cleavage by ligand aromatization/dearomatization-initiated O−O σ-bond scission. A detailed comparison of the calix[4]pyrrolato aluminates with dioxygen-related enzymology provides insights into the ISC of metal- or cofactor-free enzymes. It substantiates the importance of structural constraint and element–ligand cooperativity for the functions of aerobic life.

Cholenic acid derivative UniPR1331 impairs tumor angiogenesis via blockade of VEGF/VEGFR2 in addition to Eph/ephrin - Rusnati, Marco; Paiardi, Giulia; Tobia, Chiara; Urbinati, Chiara; Lodola, Alessio; D’Ursi, Pasqualina; Corrado, Miriam; Castelli, Riccardo; Wade, Rebecca C.; Tognolini, Massimiliano; Chiodelli, Paola (Cancer Gene Therapy, 2022)
Abstract

Second Order Finite Volume Scheme for Euler Equations with Gravity which is Well-Balanced for General Equations of State and Grid Systems - P, Berberich, Jonas; Praveen, Chandrashekar,; Christian, Klinengerg,; Röpke, Friedrich (Communications in Computational Physics, 2019)

Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices. - López, Federico; Pozzetti, Beatrice; Trettel, Steve; Strube, Michael; Wienhard, Anna (2021)

A Novel Wikipedia based Dataset for Monolingual and Cross-lingual Summarization - Fatima, Mehwish; Strube, Michael (2021)

Countering the Influence of Essay Length in Neural Essay Scoring. - Jeon, Sungho; Strube, Michael (2021)

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms - Ostaszewski, Marek; Niarakis, Anna; Mazein, Alexander; Kuperstein, Inna; Phair, Robert; Orta‐Resendiz, Aurelio; Singh, Vidisha; Aghamiri, Sara Sadat; Acencio, Marcio Luis; Glaab, Enrico; Ruepp, Andreas; Fobo, Gisela; et al. (Molecular Systems Biology, 2021)
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Gain-of-Function Variant p.Pro2555Arg of von Willebrand Factor Increases Aggregate Size through Altering Stem Dynamics. - Huck, V.; Chen, P. C.; Xu, E. R.; Tischer, A.; Klemm, U.; Aponte-Santamaria, C.; Mess, C.; Obser, T.; Kutzki, F.; Konig, G.; Denis, C. V.; Grater, F.; et al. (Thromb Haemost, 2022)
The multimeric plasma glycoprotein (GP) von Willebrand factor (VWF) is best known for recruiting platelets to sites of injury during primary hemostasis. Generally, mutations in the VWF gene lead to loss of hemostatic activity and thus the bleeding disorder von Willebrand disease. By employing cone and platelet aggregometry and microfluidic assays, we uncovered a platelet GPIIb/IIIa-dependent prothrombotic gain of function (GOF) for variant p.Pro2555Arg, located in the C4 domain, leading to an increase in platelet aggregate size. We performed complementary biophysical and structural investigations using circular dichroism spectra, small-angle X-ray scattering, nuclear magnetic resonance spectroscopy, molecular dynamics simulations on the single C4 domain, and dimeric wild-type and p.Pro2555Arg constructs. C4-p.Pro2555Arg retained the overall structural conformation with minor populations of alternative conformations exhibiting increased hinge flexibility and slow conformational exchange. The dimeric protein becomes disordered and more flexible. Our data suggest that the GOF does not affect the binding affinity of the C4 domain for GPIIb/IIIa. Instead, the increased VWF dimer flexibility enhances temporal accessibility of platelet-binding sites. Using an interdisciplinary approach, we revealed that p.Pro2555Arg is the first VWF variant, which increases platelet aggregate size and shows a shear-dependent function of the VWF stem region, which can become hyperactive through mutations. Prothrombotic GOF variants of VWF are a novel concept of a VWF-associated pathomechanism of thromboembolic events, which is of general interest to vascular health but not yet considered in diagnostics. Thus, awareness should be raised for the risk they pose. Furthermore, our data implicate the C4 domain as a novel antithrombotic drug target.
Keywords: *Gain of Function Mutation/genetics; *Genetic Variation; Hemostasis; Humans; Platelet Aggregation; Platelet Glycoprotein GPIIb-IIIa Complex/*metabolism; Protein Domains/genetics; von Willebrand Diseases/blood; von Willebrand Factor/*genetics/metabolism

Coarse-Grained Simulation of Mechanical Properties of Single Microtubules With Micrometer Length. - Zha, J.; Zhang, Y.; Xia, K.; Grater, F.; Xia, F. (Front Mol Biosci, 2020)
Microtubules are one of the most important components in the cytoskeleton and play a vital role in maintaining the shape and function of cells. Because single microtubules are some micrometers long, it is difficult to simulate such a large system using an all-atom model. In this work, we use the newly developed convolutional and K-means coarse-graining (CK-CG) method to establish an ultra-coarse-grained (UCG) model of a single microtubule, on the basis of the low electron microscopy density data of microtubules. We discuss the rationale of the micro-coarse-grained microtubule models of different resolutions and explore microtubule models up to 12-micron length. We use the devised microtubule model to quantify mechanical properties of microtubules of different lengths. Our model allows mesoscopic simulations of micrometer-level biomaterials and can be further used to study important biological processes related to microtubule function.

How multisite phosphorylation impacts the conformations of intrinsically disordered proteins. - Jin, F.; Grater, F. (PLoS Comput Biol, 2021)
Phosphorylation of intrinsically disordered proteins (IDPs) can produce changes in structural and dynamical properties and thereby mediate critical biological functions. How phosphorylation effects intrinsically disordered proteins has been studied for an increasing number of IDPs, but a systematic understanding is still lacking. Here, we compare the collapse propensity of four disordered proteins, Ash1, the C-terminal domain of RNA polymerase (CTD2'), the cytosolic domain of E-Cadherin, and a fragment of the p130Cas, in unphosphorylated and phosphorylated forms using extensive all-atom molecular dynamics (MD) simulations. We find all proteins to show V-shape changes in their collapse propensity upon multi-site phosphorylation according to their initial net charge: phosphorylation expands neutral or overall negatively charged IDPs and shrinks positively charged IDPs. However, force fields including those tailored towards and commonly used for IDPs overestimate these changes. We find quantitative agreement of MD results with SAXS and NMR data for Ash1 and CTD2' only when attenuating protein electrostatic interactions by using a higher salt concentration (e.g. 350 mM), highlighting the overstabilization of salt bridges in current force fields. We show that phosphorylation of IDPs also has a strong impact on the solvation of the protein, a factor that in addition to the actual collapse or expansion of the IDP should be considered when analyzing SAXS data. Compared to the overall mild change in global IDP dimension, the exposure of active sites can change significantly upon phosphorylation, underlining the large susceptibility of IDP ensembles to regulation through post-translational modifications.
Keywords: Amino Acid Sequence; Intrinsically Disordered Proteins/chemistry/*metabolism; Molecular Dynamics Simulation; Nuclear Magnetic Resonance, Biomolecular; Phosphorylation; Protein Conformation; Protein Processing, Post-Translational; Reproducibility of Results

ColBuilder: A server to build collagen fibril models. - Obarska-Kosinska, A.; Rennekamp, B.; Unal, A.; Grater, F. (Biophys J, 2021)
Type I collagen is the main structural component of many tissues in the human body. It provides excellent mechanical properties to connective tissue and acts as a protein interaction hub. There is thus a wide interest in understanding the properties and diverse functions of type I collagen at the molecular level. A precondition is an atomistic collagen I structure as it occurs in native tissue. To this end, we built full-atom models of cross-linked collagen fibrils by integrating the low-resolution structure of collagen fibril available from x-ray fiber diffraction with high-resolution structures of short collagen-like peptides from x-ray crystallography and mass spectrometry data. We created a Web resource of collagen models for 20 different species with a large variety of cross-link types and localization within the fibril to facilitate structure-based analyses and simulations of type I collagen in health and disease. To easily enable simulations, we provide parameters of the modeled cross-links for an Amber force field. The repository of collagen models is available at https://colbuilder.h-its.org.
Keywords: *Collagen; Collagen Type I; Connective Tissue; *Extracellular Matrix; Humans; X-Ray Diffraction

NetRAX: Accurate and Fast Maximum Likelihood Phylogenetic Network Inference ⋆ - Lutteropp, Sarah; Scornavacca, Céline; Kozlov, Alexey; Morel, Benoit; Stamatakis, Alexandros (2021)

Swarm v3: towards tera-scale amplicon clustering - Mahé, Frédéric; Czech, Lucas; Stamatakis, Alexandros; Quince, Christopher; de Vargas, Colomban; Dunthorn, Micah; Rognes, Torbjørn (Bioinformatics, 2021)

SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss - Morel, Benoit; Schade, Paul; Lutteropp, Sarah; Williams, Tom A.; Szöllősi, Gergely J.; Stamatakis, Alexandros (2021)

SPART, a versatile and standardized data exchange format for species partition information - Miralles, Aurélien; Ducasse, Jacques; Brouillet, Sophie; Flouri, Tomas; Fujisawa, Tomochika; Kapli, Paschalia; Knowles, L. Lacey; Kumari, Sangeeta; Stamatakis, Alexandros; Sukumaran, Jeet; Lutteropp, Sarah; Vences, Miguel; et al. (2021)

The wall lizards of the Balkan peninsula: Tackling questions at the interface of phylogenomics and population genomics - Psonis, Nikolaos; Antoniou, Aglaia; Karameta, Emmanouela; Darriba, Diego; Stamatakis, Alexandros; Lymberakis, Petros; Poulakakis, Nikos (Molecular Phylogenetics and Evolution, 2021)

Exploring Parallel MPI Fault Tolerance Mechanisms for Phylogenetic Inference with RAxML-NG - Hübner, Lukas; Kozlov, Alexey M.; Hespe, Demian; Sanders, Peter; Stamatakis, Alexandros (2021)

Want to track pandemic variants faster? Fix the bioinformatics bottleneck - Hodcroft, Emma B.; De Maio, Nicola; Lanfear, Rob; MacCannell, Duncan R.; Minh, Bui Quang; Schmidt, Patrick; Stamatakis, Alexandros; Goldman, Nick; Dessimoz, Christophe (Nature, 2021)

Disentangling the optical AGN and host-galaxy luminosity with a probabilistic flux variation gradient - Gianniotis, Nikos; Pozo Nuñez, F.; Polsterer, Kai (Astronomy & Astrophysics, 2021)

First-Order Geometric Multilevel Optimization for Discrete Tomography - Plier, Jan; Savarino, Fabrizio; Kočvara, Michal; Petra, Stefania (Scale Space and Variational Methods in Computer Vision, 2021)

Multiscale Approach for Computing Gated Ligand Binding from Molecular Dynamics and Brownian Dynamics Simulations - Sadiq, S. Kashif; Muniz Chicharro, Abraham; Friedrich, Patrick; Wade, Rebecca C. (Journal of Chemical Theory and Computation, 2021)

Weighing stars from birth to death: mass determination methods across the HRD - Serenelli, Aldo; Weiss, Achim; Aerts, Conny; Angelou, George C.; Baroch, David; Bastian, Nate; Beck, Paul G.; Bergemann, Maria; Bestenlehner, Joachim M.; Czekala, Ian; Elias-Rosa, Nancy; Escorza, Ana; et al. (Astronomy and Astrophysics Review, 2021)

A massive binary system with a single magnetic star - Frost, A. J.; Mahy, L.; Sana, H.; LeBouquin, J. -B.; Wade, G.; Merand, A.; Schneider, Fabian; Shenar, T.; Barbá, R. H.; Barron, J.; Bowman, D. M.; Fabry, M.; et al. (2021)

State-of-the-art evolution models for single, binary and magnetic massive stars - Schneider, Fabian (2021)

The young massive SMC cluster NGC 330 seen by MUSE. II. Multiplicity properties of the massive-star population - Bodensteiner, J.; Sana, H.; Wang, C.; Langer, N.; Mahy, L.; Banyard, G.; de Koter, A.; de Mink, S. E.; Evans, C. J.; Götberg, Y.; Patrick, L. R.; Schneider, Fabian; et al. (Astronomy and Astrophysics, 2021)

Observational evidence of coalescence as a viable cause of magnetism in massive stars - Frost, A. J.; Mahy, L.; Sana, H.; Barba, R. H.; Barron, J.; Bowman, D. M.; Fabry, M.; Bouquin, J. -B. Le; Morrell, N. I.; Marchant, P.; Merand, A.; Munoz, M.; et al. (2021)

The Tarantula Massive Binary Monitoring. V. R 144: a wind-eclipsing binary with a total mass \ensuremath≳140 M_\ensuremath⊙ - Shenar, T.; Sana, H.; Marchant, P.; Pablo, B.; Richardson, N.; Moffat, A. F. J.; Van Reeth, T.; Barbá, R. H.; Bowman, D. M.; Broos, P.; Crowther, P. A.; Clark, J. S.; et al. (Astronomy and Astrophysics, 2021)

Simulating the formation of \ensuremathη Carinae’s surrounding nebula through unstable triple evolution and stellar merger-induced eruption - Hirai, Ryosuke; Podsiadlowski, Philipp; Owocki, Stanley P.; Schneider, Fabian; Smith, Nathan (Monthly Notices of the Royal Astronomical Society, 2021)

Comparison of Machine Learning Methods for Predicting Employee Absences - Jayme, Alejandra; Lösel, Philipp; Heuveline, Vincent (Preprint Series of the Engineering Mathematics and Computing Lab, 2021)

Spatial Effect on Separatrix of Two-Cell System and Parameter Sensitivity Analysis - Song, Chen; Roller, Jonas; Ponce-Bobadilla, Ana Victoria; Palacio-Escat, Nicolas; Saez-Rodriguez, Julio; Heuveline, Vincent (Preprint Series of the Engineering Mathematics and Computing Lab, 2021)

Mathematical modeling of multiple pathways in colorectal carcinogenesis using dynamical systems with Kronecker structure - Haupt, Saskia; Zeilmann, Alexander; Ahadova, Aysel; Bläker, Hendrik; Doeberitz, Magnus von Knebel; Kloor, Matthias; Heuveline, Vincent (PLOS Computational Biology, 2021)
Like many other types of cancer, colorectal cancer (CRC) develops through multiple pathways of carcinogenesis. This is also true for colorectal carcinogenesis in Lynch syndrome (LS), the most common inherited CRC syndrome. However, a comprehensive understanding of the distribution of these pathways of carcinogenesis, which allows for tailored clinical treatment and even prevention, is still lacking. We suggest a linear dynamical system modeling the evolution of different pathways of colorectal carcinogenesis based on the involved driver mutations. The model consists of different components accounting for independent and dependent mutational processes. We define the driver gene mutation graphs and combine them using the Cartesian graph product. This leads to matrix components built by the Kronecker sum and product of the adjacency matrices of the gene mutation graphs enabling a thorough mathematical analysis and medical interpretation. Using the Kronecker structure, we developed a mathematical model which we applied exemplarily to the three pathways of colorectal carcinogenesis in LS. Beside a pathogenic germline variant in one of the DNA mismatch repair (MMR) genes, driver mutations in APC, CTNNB1, KRAS and TP53 are considered. We exemplarily incorporate mutational dependencies, such as increased point mutation rates after MMR deficiency, and based on recent experimental data, biallelic somatic CTNNB1 mutations as common drivers of LS-associated CRCs. With the model and parameter choice, we obtained simulation results that are in concordance with clinical observations. These include the evolution of MMR-deficient crypts as early precursors in LS carcinogenesis and the influence of variants in MMR genes thereon. The proportions of MMR-deficient and MMR-proficient APC-inactivated crypts as first measure for the distribution among the pathways in LS-associated colorectal carcinogenesis are compatible with clinical observations. The approach provides a modular framework for modeling multiple pathways of carcinogenesis yielding promising results in concordance with clinical observations in LS CRCs.

A computational model for investigating the evolution of colonic crypts during Lynch syndrome carcinogenesis - Haupt, Saskia; Gleim, Nils; Ahadova, Aysel; Bläker, Hendrik; Doeberitz, Magnus von Knebel; Kloor, Matthias; Heuveline, Vincent (Computational and Systems Oncology, 2021)
Abstract Lynch syndrome (LS), the most common inherited colorectal cancer (CRC) syndrome, increases the cancer risk in affected individuals. LS is caused by pathogenic germline variants in one of the DNA mismatch repair (MMR) genes, complete inactivation of which causes numerous mutations in affected cells. As CRC is believed to originate in colonic crypts, understanding the intra-crypt dynamics caused by mutational processes is essential for a complete picture of LS CRC and may have significant implications for cancer prevention. We propose a computational model describing the evolution of colonic crypts during LS carcinogenesis. Extending existing modeling approaches for the non-Lynch scenario, we incorporated MMR deficiency and implemented recent experimental data demonstrating that somatic CTNNB1 mutations are common drivers of LS-associated CRCs, if affecting both alleles of the gene. Further, we simulated the effect of different mutations on the entire crypt, distinguishing non-transforming and transforming mutations. As an example, we analyzed the spread of mutations in the genes APC and CTNNB1, which are frequently mutated in LS tumors, as well as of MMR deficiency itself. We quantified each mutation's potential for monoclonal conversion and investigated the influence of the cell location and of stem cell dynamics on mutation spread. The in silico experiments underline the importance of stem cell dynamics for the overall crypt evolution. Further, simulating different mutational processes is essential in LS since mutations without survival advantages (the MMR deficiency-inducing second hit) play a key role. The effect of other mutations can be simulated with the proposed model. Our results provide first mathematical clues towards more effective surveillance protocols for LS carriers.

Watching people decide: decision prediction using heatmaps of reading of a decision-support document - Ghosh, Sucheta; Wronski, Pamela; Koetsenruijter, Jan; Müller, Wolfgang; Wensing, Michel (Journal of Vision, 2021)

Electrostatic interactions contribute to the control of intramolecular thiol-disulfide isomerization in a protein. - Maag, D.; Putzu, M.; Gomez-Flores, C. L.; Grater, F.; Elstner, M.; Kubar, T. (Phys Chem Chem Phys, 2021)
The roles of structural factors and of electrostatic interactions with the environment on the outcome of thiol-disulfide exchange reactions were investigated in a mutated immunoglobulin domain (I27*) under mechanical stress. An extensive ensemble of molecular dynamics trajectories was generated by means of QM/MM simulations for a total sampling of 5.7 mus. A significant number of thiol-disulfide exchanges were observed, and the Cys32 thiolate preferred to attack Cys55 over Cys24, in agreement with previous experimental and computational studies. The structural features as well as electronic structures of the thiol-disulfide system along the reaction were analyzed, as were the electrostatic interactions with the environment. The previous findings of better accessibility of Cys55 were confirmed. Additionally, the reaction was found to be directed by the electrostatic interactions of the involved sulfur atoms with the molecular environment. The relationships of atomic charges, which stem from the electrostatic interactions, lead to the kinetic preference of the attack on Cys55. Further, QM/MM metadynamics simulations of thiol-disulfide exchange in a small model system with varied artificial external electric potentials revealed changes in reaction kinetics of the same magnitude as in I27*. Therefore, the electrostatic interactions are confirmed to play a role in the regioselectivity of the thiol-disulfide exchange reactions in the protein.
Keywords: Disulfides/*chemistry; Isomerism; Kinetics; *Molecular Dynamics Simulation; Proteins/*chemistry; Quantum Theory; Static Electricity; Sulfhydryl Compounds/*chemistry

Assessing predictive performance: From precipitation forecasts over the tropics to receiver operating characteristic curves and back - Vogel, Peter (2019)

Theory and methodology of scoring functions: Tail properties, interval forecasts, and point processes - Brehmer, Jonas R. (2020)

The AIMe registry for artificial intelligence in biomedical research - Matschinske, Julian; Alcaraz, Nicolas; Benis, Arriel; Golebiewski, Martin; Grimm, Dominik G.; Heumos, Lukas; Kacprowski, Tim; Lazareva, Olga; List, Markus; Louadi, Zakaria; Pauling, Josch K.; Pfeifer, Nico; et al. (Nature Methods, 2021)

Ten Simple Rules for Sharing Experimental and Clinical Data with the Modeling Community - König, Matthias; Grzegorzewski, Jan; Golebiewski, Martin; Hermjakob, Henning; Hucka, Mike; Olivier, Brett; Keating, Sarah; Nickerson, David; Schreiber, Falk; Sheriff, Rahuman; Waltemath, Dagmar (2021)

SABIO-RK, von Daten in der Publikation zur Suchlösung für Spezialisten - Müller, Wolfgang; Bittkowski, Meik; Golebiewski, Martin; Kania, Renate; Rey, Maja; Weidemann, Andreas; Wittig, Ulrike (Datenbank-Spektrum, 2017)

A brief history of COMBINE - Myers, Chris J.; Bader, Gary; Gleeson, Padraig; Golebiewski, Martin; Hucka, Michael; Le Novere, Nicolas; Nickerson, David P.; Schreiber, Falk; Waltemath, Dagmar (2017 Winter Simulation Conference (WSC), 2017)

NORM-SYS - harmonizing standardization processes for model and data exchange in systems biology - Regierer, Babette; Hollmann, Susanne; Golebiewski, Martin (EMBnet.journal, 2016)

COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project - Bergmann, Frank T; Adams, Richard; Moodie, Stuart; Cooper, Jonathan; Glont, Mihai; Golebiewski, Martin; Hucka, Michael; Laibe, Camille; Miller, Andrew K; Nickerson, David P; Olivier, Brett G; Rodriguez, Nicolas; et al. (BMC Bioinformatics, 2014)

Meeting report from the fourth meeting of the Computational Modeling in Biology Network (COMBINE) - Waltemath, Dagmar; Bergmann, Frank T.; Chaouiya, Claudine; Czauderna, Tobias; Gleeson, Padraig; Goble, Carole; Golebiewski, Martin; Hucka, Michael; Juty, Nick; Krebs, Olga; Le Novère, Nicolas; Mi, Huaiyu; et al. (Standards in Genomic Sciences, 2014)

Path2Models: large-scale generation of computational models from biochemical pathway maps - Büchel, Finja; Rodriguez, Nicolas; Swainston, Neil; Wrzodek, Clemens; Czauderna, Tobias; Keller, Roland; Mittag, Florian; Schubert, Michael; Glont, Mihai; Golebiewski, Martin; van Iersel, Martijn; Keating, Sarah; et al. (BMC Systems Biology, 2013)

FAIRsharing as a community approach to standards, repositories and policies - Sansone, Susanna-Assunta; McQuilton, Peter; Rocca-Serra, Philippe; Gonzalez-Beltran, Alejandra; Izzo, Massimiliano; Lister, Allyson L.; Thurston, Milo (Nature Biotechnology, 2019)

Controlled vocabularies and semantics in systems biology - Courtot, Mélanie; Juty, Nick; Knüpfer, Christian; Waltemath, Dagmar; Zhukova, Anna; Dräger, Andreas; Dumontier, Michel; Finney, Andrew; Golebiewski, Martin; Hastings, Janna; Hoops, Stefan; Keating, Sarah; et al. (Molecular Systems Biology, 2011)

SBML2LATEX: Conversion of SBML files into human-readable reports - Drager, A.; Planatscher, H.; Motsou Wouamba, D.; Schroder, A.; Hucka, M.; Endler, L.; Golebiewski, Martin; Müller, Wolfgang; Zell, A. (Bioinformatics, 2009)

Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases. - Mayer, G.; Muller, W.; Schork, K.; Uszkoreit, J.; Weidemann, A.; Wittig, U.; Rey, M.; Quast, C.; Felden, J.; Glockner, F. O.; Lange, M.; Arend, D.; et al. (Brief Bioinform, 2021)
This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusable) data principles in a large distributed bioinformatics infrastructure. We address the challenge of heterogeneity of wet lab technologies, data, metadata, software, computational workflows and the levels of implementation and monitoring of FAIR principles within the different bioinformatics sub-disciplines joint in de.NBI. On the one hand, this broad service landscape and the excellent network of experts are a strong basis for the development of useful research data management plans. On the other hand, the large number of tools and techniques maintained by distributed teams renders FAIR compliance challenging.
Keywords: Data Management/*methods; Genome, Human; High-Throughput Nucleotide Sequencing; Humans; International Cooperation; *Metadata; *Neural Networks, Computer; Phenotype; Plants/genetics; Proteome; Proteomics/*methods; Self-Assessment; *Software; Workflow

SABIO-RK: A data warehouse for biochemical reactions and their kinetics - Krebs, Olga; Golebiewski, Martin; Kania, Renate; Mir, Saqib; Saric, Jasmin; Weidemann, Andreas; Wittig, Ulrike; Rojas, Isabel (Journal of Integrative Bioinformatics, 2007)

SABIO-RK: Integration and Curation of Reaction Kinetics Data - Wittig, Ulrike; Golebiewski, Martin; Kania, Renate; Krebs, Olga; Mir, Saqib; Weidemann, Andreas; Anstein, Stefanie; Saric, Jasmin; Rojas, Isabel (Data Integration in the Life Sciences, 2006)

Longitudinal strand ordering leads to shear thinning in Nafion. - Michelarakis, N.; Franz, F.; Gkagkas, K.; Grater, F. (Phys Chem Chem Phys, 2021)
Proton-exchange membrane fuel cells (PEMFC) offer a promising energy generation alternative for a wide range of technologies thanks to their ecological friendliness and unparalleled efficiency. At the heart of these electrochemical cells lies the membrane electrode assembly with its most important energy conversion components, the Proton Exchange Membrane. This component is created through the use of printing techniques and Nafion inks. The physicochemical properties of the ink, such as its viscosity under shear, are critical for the finished product. In this work we present non-equilibrium Molecular Dynamics simulations using a MARTINI based coarse-grained model for Nafion to understand the mechanism governing the shear viscosity of Nafion solutions. By simulating a Couette flow and calculating density maps of the Nafion chains in these simulations we shed light on the process that leads to the experimentally observed shear thinning effects of Nafion solutions under flow. We observe rod-shaped Nafion microstructures, 3 nm in size on average, when shear flow is absent or low. Higher shear rates instead break these structures and align Nafion strands along the direction of the flow, resulting in lower shear viscosities. Our work paves the way for a deeper understanding of the dynamic and mechanical properties of Nafion including studies of more complex CL and PEM inks.

Kinetic and structural roles for the surface in guiding SAS-6 self-assembly to direct centriole architecture. - Banterle, N.; Nievergelt, A. P.; de Buhr, S.; Hatzopoulos, G. N.; Brillard, C.; Andany, S.; Hubscher, T.; Sorgenfrei, F. A.; Schwarz, U. S.; Grater, F.; Fantner, G. E.; Gonczy, P. (Nat Commun, 2021)
Discovering mechanisms governing organelle assembly is a fundamental pursuit in biology. The centriole is an evolutionarily conserved organelle with a signature 9-fold symmetrical chiral arrangement of microtubules imparted onto the cilium it templates. The first structure in nascent centrioles is a cartwheel, which comprises stacked 9-fold symmetrical SAS-6 ring polymers emerging orthogonal to a surface surrounding each resident centriole. The mechanisms through which SAS-6 polymerization ensures centriole organelle architecture remain elusive. We deploy photothermally-actuated off-resonance tapping high-speed atomic force microscopy to decipher surface SAS-6 self-assembly mechanisms. We show that the surface shifts the reaction equilibrium by ~10(4) compared to solution. Moreover, coarse-grained molecular dynamics and atomic force microscopy reveal that the surface converts the inherent helical propensity of SAS-6 polymers into 9-fold rings with residual asymmetry, which may guide ring stacking and impart chiral features to centrioles and cilia. Overall, our work reveals fundamental design principles governing centriole assembly.
Keywords: Cell Cycle Proteins/*chemistry; Centrioles/*chemistry; Chlamydomonas reinhardtii/chemistry; Kinetics; Microscopy, Atomic Force; Models, Chemical; Molecular Dynamics Simulation; Organelle Biogenesis; Protein Conformation; Protein Multimerization

From spontaneous to strategic natural window ventilation: Improving indoor air quality in Swiss schools - Vassella, Claudia C.; Koch, Jeremy; Henzi, Alexander; Jordan, Alexander I.; Waeber, Roger; Iannaccone, Reto; Charrière, Roland (International Journal of Hygiene and Environmental Health, 2021)

Asteroseismic Inference of the Central Structure in a Subgiant Star - Bellinger, Earl P.; Basu, Sarbani; Hekker, Saskia; Christensen-Dalsgaard, Jørgen; Ball, Warrick H. (The Astrophysical Journal, 2021)
Asteroseismic measurements enable inferences of the underlying stellar structure, such as the density and the speed of sound at various points within the interior of the star. This provides an opportunity to test stellar evolution theory by assessing whether the predicted structure of a star agrees with the measured structure. Thus far, this kind of inverse analysis has only been applied to the Sun and three solar-like main-sequence stars. Here we extend the technique to stars on the subgiant branch, and apply it to one of the best-characterized subgiants of the Kepler mission, HR 7322. The observation of mixed oscillation modes in this star facilitates inferences of the conditions of its inert helium core, nuclear-burning hydrogen shell, and the deeper parts of its radiative envelope. We find that despite significant differences in the mode frequencies, the structure near to the center of this star does not differ significantly from the predicted structure.

TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star - Addison, Brett C; Wright, Duncan J; Nicholson, Belinda A; Cale, Bryson; Mocnik, Teo; Huber, Daniel; Plavchan, Peter; Wittenmyer, Robert A; Vanderburg, Andrew; Chaplin, William J; Chontos, Ashley; Clark, Jake T; et al. (Monthly Notices of the Royal Astronomical Society, 2021)
We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASA's Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the MINERVA-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of MP = 0.138 ± 0.023 MJ (43.9 ± 7.3 M⊕ ), a radius of RP = 0.639 ± 0.013 RJ (7.16 ± 0.15 R⊕ ), bulk density of 0.65+0.12−0.11 (cgs), and period 18.38818+0.00085−0.00084 days . TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M* = 1.390 ± 0.046 Msun , R* = 1.888 ± 0.033 Rsun , Teff = 6075 ± 90 K , and vsin i = 11.3 ± 0.5 km s-1. Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a ∼71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (∼100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems.

Asteroseismology of luminous red giants with Kepler – II. Dependence of mass-loss on pulsations and radiation - Yu, Jie; Hekker, Saskia; Bedding, Timothy R; Stello, Dennis; Huber, Daniel; Gizon, Laurent; Khanna, Shourya; Bi, Shaolan (Monthly Notices of the Royal Astronomical Society, 2021)
Mass-loss by red giants is an important process to understand the final stages of stellar evolution and the chemical enrichment of the interstellar medium. Mass-loss rates are thought to be controlled by pulsation-enhanced dust-driven outflows. Here, we investigate the relationships between mass-loss, pulsations, and radiation, using 3213 luminous Kepler red giants and 13 5000 ASAS-SN semiregulars and Miras. Mass-loss rates are traced by infrared colours using 2MASS and Wide-field Infrared Survey Explorer(WISE) and by observed-to-model WISE fluxes, and are also estimated using dust mass-loss rates from literature assuming a typical gas-to-dust mass ratio of 400. To specify the pulsations, we extract the period and height of the highest peak in the power spectrum of oscillation. Absolute magnitudes are obtained from the 2MASS Ks band and the Gaia DR2 parallaxes. Our results follow. (i) Substantial mass-loss sets in at pulsation periods above ∼60 and ∼100 d, corresponding to Asymptotic-Giant-Branch stars at the base of the period-luminosity sequences C' and C. (ii) The mass-loss rate starts to rapidly increase in semiregulars for which the luminosity is just above the red-giant-branch tip and gradually plateaus to a level similar to that of Miras. (iii) The mass-loss rates in Miras do not depend on luminosity, consistent with pulsation-enhanced dust-driven winds. (iv) The accumulated mass-loss on the red giant branch consistent with asteroseismic predictions reduces the masses of red-clump stars by 6.3 per cent, less than the typical uncertainty on their asteroseismic masses. Thus mass-loss is currently not a limitation of stellar age estimates for galactic archaeology studies.

A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave - Bracher, Johannes; Wolffram, Daniel; Deuschel, Jannik; Görgen, Konstantin; Ketterer, Jakob L.; Ullrich, Alexander; Abbott, Sam; Barbarossa, Maria Vittoria; Bertsimas, Dimitris; Bhatia, Sangeeta; Bodych, Marcin; Bosse, Nikos I.; et al. (Nature Communications, 2021)

Characterizing the optimal solutions to the isotonic regression problem for identifiable functionals - Jordan, Alexander I.; Mühlemann, Anja; Ziegel, Johanna F. (Annals of the Institute of Statistical Mathematics, 2022)

Isotonic distributional regression - Henzi, Alexander; Ziegel, Johanna F.; Gneiting, Tilmann (Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2021)

Interpretation of point forecasts with unknown directive - Schmidt, Patrick; Katzfuss, Matthias; Gneiting, Tilmann (Journal of Applied Econometrics, 2021)

Novel multivariate quantile mapping methods for ensemble post-processing of medium-range forecasts - Whan, Kirien; Zscheischler, Jakob; Jordan, Alexander I.; Ziegel, Johanna F. (Weather and Climate Extremes, 2021)

Scoring interval forecasts: Equal-tailed, shortest, and modal interval - Brehmer, Jonas R.; Gneiting, Tilmann (Bernoulli, 2021)

Forecast encompassing tests for the expected shortfall - Dimitriadis, Timo; Schnaitmann, Julie (International Journal of Forecasting, 2021)

Stable reliability diagrams for probabilistic classifiers - Dimitriadis, Timo; Gneiting, Tilmann; Jordan, Alexander I. (Proceedings of the National Academy of Sciences, 2021)

Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA) - Gneiting, Tilmann; Walz, Eva-Maria (Machine Learning, 2022)

Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison - Schulz, Benedikt; Lerch, Sebastian (Monthly Weather Review, 2022)

Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting - Schulz, Benedikt; Ayari, Mehrez El; Lerch, Sebastian; Baran, Sándor (Solar Energy, 2021)

Encompassing tests for value at risk and expected shortfall multistep forecasts based on inference on the boundary - Dimitriadis, Timo; Liu, Xiaochun; Schnaitmann, Julie (Journal of Financial Econometrics, 2023)

Machine learning for total cloud cover prediction - Baran, Ágnes; Lerch, Sebastian; Ayari, Mehrez El; Baran, Sándor (Neural Computing and Applications, 2021)

A construction principle for proper scoring rules - Brehmer, Jonas (Proceedings of the American Mathematical Society, Series B, 2021)

Survey-based forecast distributions for Euro Area growth and inflation: Ensembles versus histograms - Krüger, Fabian (Empirical Economics, 2017)

Using entropic tilting to combine BVAR forecasts with external nowcasts - Krüger, Fabian; Clark, Todd E.; Ravazzolo, Francesco (Journal of Business & Economic Statistics, 2017)

Ensemble calibration with preserved correlations: Unifying and comparing ensemble copula coupling and member‐by‐member postprocessing - Schefzik, Roman (Quarterly Journal of the Royal Meteorological Society, 2017)

Trends in the predictive performance of raw ensemble weather forecasts - Hemri, S.; Scheuerer, M.; Pappenberger, F.; Bogner, K.; Haiden, T. (Geophysical Research Letters, 2014)

Probabilistic forecasting - Gneiting, Tilmann; Katzfuss, Matthias (Annual Review of Statistics and Its Application, 2014)

Evaluating predictive performance - Scheuerer, Michael; Gneiting, Tilmann (Lecture Notes in Earth System Sciences, 2014)

Copula calibration - Ziegel, Johanna F.; Gneiting, Tilmann (Electronic Journal of Statistics, 2014)

Uncertainty quantification in complex simulation models using ensemble copula coupling - Schefzik, Roman; Thorarinsdottir, Thordis L.; Gneiting, Tilmann (Statistical Science, 2013)

Probabilistic wind vector forecasting using ensembles and Bayesian model averaging - Sloughter, J M; Gneiting, Tilmann; Raftery, A E (Monthly Weather Review, 2013)

Combining predictive distributions - Gneiting, Tilmann; Ranjan, Roopesh (Electronic Journal of Statistics, 2013)

Using proper divergence functions to evaluate climate models - Thorarinsdottir, Thordis L.; Gneiting, Tilmann; Gissibl, Nadine (SIAM/ASA Journal on Uncertainty Quantification, 2013)

Consistent scoring functions for quantiles - Grant, Kyrill; Gneiting, Tilmann (Institute of Mathematical Statistics Collections, 2013)

Robust forecast evaluation of expected shortfall - Ziegel, Johanna F; Krüger, Fabian; Jordan, Alexander I.; Fasciati, Fernando (Journal of Financial Econometrics, 2020)

Regression-based expected shortfall backtesting - Bayer, Sebastian; Dimitriadis, Timo (Journal of Financial Econometrics, 2022)

Evaluating epidemic forecasts in an interval format - Bracher, Johannes; Ray, Evan L.; Gneiting, Tilmann; Reich, Nicholas G. (PLOS Computational Biology, 2021)

Statistical forecasts for the occurrence of precipitation outperform global models over northern tropical Africa - Vogel, Peter; Knippertz, Peter; Gneiting, Tilmann; Fink, Andreas H.; Klar, Manuel; Schlueter, Andreas (Geophysical Research Letters, 2021)

Predictive inference based on Markov chain Monte Carlo output - Krüger, Fabian; Lerch, Sebastian; Thorarinsdottir, Thordis; Gneiting, Tilmann (International Statistical Review, 2021)

Skill of global raw and postprocessed ensemble predictions of rainfall in the tropics - Vogel, Peter; Knippertz, Peter; Fink, Andreas H.; Schlueter, Andreas; Gneiting, Tilmann (Weather and Forecasting, 2020)

The affinely invariant distance correlation - Dueck, Johannes; Edelmann, Dominic; Gneiting, Tilmann; Richards, Donald (Bernoulli, 2014)

Strictly and non-strictly positive definite functions on spheres - Gneiting, Tilmann (Bernoulli, 2013)

EnzymeML-a data exchange format for biocatalysis and enzymology. - Range, J.; Halupczok, C.; Lohmann, J.; Swainston, N.; Kettner, C.; Bergmann, F. T.; Weidemann, A.; Wittig, U.; Schnell, S.; Pleiss, J. (FEBS J, 2022)
EnzymeML is an XML-based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.
Keywords: Biocatalysis; Databases, Factual; *Software

Physically coherent probabilistic weather forecasts using multivariate discrete copula-based ensemble postprocessing methods - Schefzik, Roman (2015)

An IMERG-based optimal extended probabilistic climatology (EPC) as a benchmark ensemble forecast for precipitation in the tropics and subtropics - Walz, Eva-Maria; Maranan, Marlon; van der Linden, Roderick; Fink, Andreas H.; Knippertz, Peter (Weather and Forecasting, 2021)

Receiver operating characteristic (ROC) curves: Equivalences, beta model, and minimum distance estimation - Gneiting, Tilmann; Vogel, Peter (Machine Learning, 2022)

Metallicity-dependent nucleosynthetic yields of Type Ia supernovae originating from double detonations of sub- M Ch white dwarfs - Gronow, Sabrina; Côté, Benoit; Lach, Florian; Seitenzahl, Ivo R.; Collins, Christine E.; Sim, Stuart A.; Röpke, Friedrich (Astronomy & Astrophysics, 2021)

Observational signatures of the surviving donor star in the double-detonation model of Type Ia supernovae - Liu, Zheng-Wei; Röpke, Friedrich; Zeng, Yaotian; Heger, Alexander (Astronomy & Astrophysics, 2021)

Multidimensional low-Mach number time-implicit hydrodynamic simulations of convective helium shell burning in a massive star - Horst, Leonhard; Hirschi, R.; Edelmann, P. V. F.; Andrássy, Róbert; Röpke, Friedrich (Astronomy & Astrophysics, 2021)

Well-balanced treatment of gravity in astrophysical fluid dynamics simulations at low Mach numbers - Edelmann, P. V. F.; Horst, Leonhard; Berberich, J. P.; Andrássy, Róbert; Higl, Johann; Leidi, G.; Klingenberg, C.; Röpke, Friedrich (Astronomy & Astrophysics, 2021)

Double detonations of sub-M Ch CO white dwarfs: variations in Type Ia supernovae due to different core and He shell masses - Gronow, Sabrina; Collins, Christine E.; Sim, Stuart A.; Röpke, Friedrich (Astronomy & Astrophysics, 2021)

Collective velocity broadening from gravity waves as a plausible mechanism for macroturbulence in massive stars - Bowman, D. M.; Burssens, S.; Simón-Dı́az, S.; Edelmann, P. V. F.; Rogers, T. M.; Horst, Leonhard; Röpke, Friedrich; Aerts, C. (2021)

Vorhersagen sind schwer, vor allem die Zukunft betreffend: Kurzzeitprognosen in der Pandemie - Bracher, Johannes; Wolffram, Daniel; Gneiting, Tilmann; Schienle, Melanie (Mitteilungen der Deutschen Mathematiker-Vereinigung, 2021)

SPART: A versatile and standardized data exchange format for species partition information - Miralles, Aurélien; Ducasse, Jacques; Brouillet, Sophie; Flouri, Tomas; Fujisawa, Tomochika; Kapli, Paschalia; Knowles, L. Lacey; Kumari, Sangeeta; Stamatakis, Alexandros; Sukumaran, Jeet; Lutteropp, Sarah; Vences, Miguel; et al. (Molecular Ecology Resources, 2022)

RAxML Grove: An empirical Phylogenetic Tree Database - Höhler, Dimitri; Pfeiffer, Wayne; Ioannidis, Vassilios; Stockinger, Heinz; Stamatakis, Alexandros (2021)

Efficient Memory Management in Likelihood-based Phylogenetic Placement - Barbera, Pierre; Stamatakis, Alexandros (2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2021)

High-Performance approaches for Phylogenetic Placement, and its application to species and diversity quantification - Barbera, Pierre
In recent years, advances in high-throughput genetic sequencing, coupled with the ongoing exponential growth and availability of computational resources, have enabled entirely new approaches in the biological sciences. It is now possible to perform broad sequencing of the genetic content of entire communities of organisms from individual environmental samples. Such methods are particularly relevant to microbiology. The field was previously largely constrained to the study of those microbes that could be cultured in the laboratory (i.e., in vitro), which represents a small fraction of the diversity observed in nature.

Empirical Numerical Properties of Maximum Likelihood Phylogenetic Inference - Haag, Julia
Phylogenetic trees represent hypothetical evolutionary relationships between organisms. Approaches for inferring phylogenetic trees include the Maximum Likelihood (ML) method. This method relies on numerical optimization routines that use internal numerical thresholds. We analyze the influence of these thresholds on the likelihood scores and runtimes of tree inferences for the ML inference tools RAxML-NG, IQ-Tree, and FastTree. We analyze 22 empirical datasets and show that we can speed up the tree inference in RAxML-NG and IQ-Tree by changing the default values of two such numerical thresholds. Using 15 additional simulated datasets, we show that these changes do not affect the accuracy of the inferred phylogenetic trees. For RAxML-NG, increasing the likelihood thresholds lh_epsilon and spr_lh_epsilon to 10 and 103 respectively results in an average speedup of 1.9 ± 0.6. Increasing the likelihood threshold lh_epsilon in IQ-Tree results in an average speedup of 1.3 ± 0.4. In addition to the numerical analysis, we attempt to predict the difficulty of datasets, with the aim of preventing an unnecessarily large number of tree inferences for datasets that are easy to analyze. We present our prediction experiments and discuss why this task proved to be more challenging than anticipated.

Algorithms, load balancing strategies, and dynamic kernels for large-scale phylogenetic tree inference under Maximum Likelihood - Morel, Benoit
Phylogenetics, the study of evolutionary relationships among biological entities, plays an essential role in biological and medical research. Its applications range from answering fundamental questions, such as understanding the origin of life, to solving more practical problems, such as tracking pandemics in real time. Nowadays, phylogenetic trees are typically inferred from molecular data, via likelihood-based methods. Those methods strive to find the tree that maximizes a likelihood score under a given stochastic model of sequence evolution. This work focuses on the inference of species as well as gene phylogenetic trees. Species evolve through speciation and extinction events. Genes evolve through events such as gene duplication, gene loss, and horizontal gene transfer. Both processes are strongly correlated, because genes belong to species and evolve within their genomes. One can deploy models of gene evolution and to exploit this correlation between species and gene evolutionary histories, in order to improve the accuracy of phylogenetic tree inference methods. However, the most widely used phylogenetic tree inference methods disregard these phenomena and focus on models of sequence evolution only. In addition, current maximum likelihood methods are computationally expensive. This is particularly challenging as the community faces a dramatically growing amount of available molecular data, due to recent advances in sequencing technologies. To handle this data avalanche, we urgently need tools that offer faster algorithms, as well as efficient parallel implementations. In this thesis, I develop new maximum likelihood methods, that explicitly model the relationships between species and gene histories, in order to infer more accurate phylogenetic trees. Those methods employ both, new heuristics, and dedicated parallelization schemes, in order to accelerate the inference process. My first project, ParGenes, is a parallel software pipeline for inferring gene family trees from a set of per-gene multiple sequence alignments. For each input alignment, it determines the best-fit model of sequence evolution, and subsequently searches for the gene family tree with the highest likelihood under this model. To this end, ParGenes uses several state-of-the-art tools, and runs them in parallel using a novel scheduling strategy. My second project, SpeciesRax, is a method for inferring a rooted species tree from a set of unrooted gene family trees. SpeciesRax strives to find the rooted species tree that maximizes the likelihood score under a dedicated model of gene evolution, that accounts for gene duplication, gene loss, and horizontal gene transfer. In addition, I introduce a new method for assessing the confidence in the resulting species tree, as well as a novel method for estimating its branch lengths. My third project, GeneRax, is a novel maximum likelihood method for gene family tree inference. GeneRax takes as input a rooted species tree as well as a set of (per-gene) multiple sequence alignments, and outputs one gene family tree per input alignment. To this end, I introduce the so-called joint likelihood function, which combines both, a model of sequence evolution, and a model of gene evolution. In addition, GeneRax can estimate the pattern of gene duplication, gene loss, and horizontal gene transfer events that occured along the input species tree.

The binding of heparin to spike glycoprotein inhibits SARS-CoV-2 infection by three mechanisms - Paiardi, Giulia; Richter, Stefan; Oreste, Pasqua; Urbinati, Chiara; Rusnati, Marco; Wade, Rebecca C. (Journal of Biological Chemistry, 2022)

Phosphorylation tunes elongation propensity and cohesiveness of INCENP's intrinsically disordered region. - Martin, I. M.; Aponte-Santamaria, C.; Schmidt, L.; Hedtfeld, M.; Iusupov, A.; Musacchio, A.; Grater, F. (J Mol Biol, 2022)
The inner centromere protein, INCENP, is crucial for correct chromosome segregation during mitosis. It connects the kinase Aurora B to the inner centromere allowing this kinase to dynamically access its kinetochore targets. However, the function of its central, 440-residue long intrinsically disordered region (IDR) and its multiple phosphorylation sites is unclear. Here, we determined the conformational ensemble of INCENP's IDR, systematically varying the level of phosphorylation, using all-atom and coarse-grain molecular dynamics simulations. Our simulations show that phosphorylation expands INCENP's IDR, both locally and globally, mainly by increasing its overall net charge. The disordered region undergoes critical globule-to-coil conformational transitions and the transition temperature non-monotonically depends on the degree of phosphorylation, with a mildly phosphorylated case of neutral net charge featuring the highest collapse propensity. The IDR transitions from a multitude of globular states, accompanied by several specific internal contacts that reduce INCENP length by loop formation, to weakly interacting and highly extended coiled conformations. Phosphorylation critically shifts the population between these two regimes. It thereby influences cohesiveness and phase behavior of INCENP IDR assemblies, a feature presumably relevant for INCENP's function in the chromosomal passenger complex. Overall, we propose the disordered region of INCENP to act as a phosphorylation-regulated and length-variable component, within the previously defined "dog-leash" model, that thereby regulates how Aurora B reaches its targets for proper chromosome segregation.
Keywords: Aurora Kinase B/metabolism; Chromosomal Proteins, Non-Histone/*chemistry/*metabolism; Humans; Intrinsically Disordered Proteins/*chemistry/metabolism; Molecular Dynamics Simulation; Phase Transition; Phosphorylation; Protein Conformation, alpha-Helical

On testing equal conditional predictive ability under measurement error - Hoga, Yannick; Dimitriadis, Timo (Journal of Business & Economic Statistics, 2023)

Combining dictionary- and rule-based approximate entity linking with tuned BioBERT - Mobasher, Ghadeer; Mertová, Lukrécia; Ghosh, Sucheta; Krebs, Olga; Heinlein, Bettina; Müller, Wolfgang (2021)
Chemical named entity recognition (NER) is a significant step for many downstream applications like entity linking for the chemical text-mining pipeline. However, the identification of chemical entities in a biomedical text is a challenging task due to the diverse morphology of chemical entities and the different types of chemical nomenclature. In this work, we describe our approach that was submitted for BioCreative version 7 challenge Track 2, focusing on the ‘Chemical Identification’ task for identifying chemical entities and entity linking, using MeSH. For this purpose, we have applied a two-stage approach as follows (a) usage of fine-tuned BioBERT for identification of chemical entities (b) semantic approximate search in MeSH and PubChem databases for entity linking. There was some friction between the two approaches, as our rule-based approach did not harmonise optimally with partially recognized words forwarded by the BERT component. For our future work, we aim to resolve the issue of the artefacts arising from BERT tokenizers and develop joint learning of chemical named entity recognition and entity linking using pre-trained transformer-based models and compare their performance with our preliminary approach. Next, we will improve the efficiency of our approximate search in reference databases during entity linking. This task is non-trivial as it entails determining similarity scores of large sets of trees with respect to a query tree. Ideally, this will enable flexible parametrization and rule selection for the entity linking search.

Assessing ML-database augmentation approaches for Druggability Score calculations in TRAPP-pocket - Marinis, Pierre-Vincenzo De (2021)

Comparison of ligand docking to the AMPAR-TARP interaction site between different isoforms - Messner, Lena (2021)

Multi-Resolution Simulation Study of CYP 2B4 to Investigate Complex Formation with Human NADPH-Cytochrome P450 Oxidoreductase in Lipid Bilayer - Han, Sungho Bosco (2021)

The effects of the linker-DNA on linker histone positioning: a single-pair FRET study from mono to trichromatosomes - De, Madhura (2021)

Molecular Dynamics Simulation of a Mammalian Cytochrome P450 Protein and its Interaction with Substrates and Redox-Partners - Teuffel, Jonathan (2022)

The Non-phosphorylating Glyceraldehyde-3-Phosphate Dehydrogenase GapN Is a Potential New Drug Target in Streptococcus pyogenes - Eisenberg, Philip; Albert, Leon; Teuffel, Jonathan; Zitzow, Eric; Michaelis, Claudia; Jarick, Jane; Sehlke, Clemens; Große, Lisa; Bader, Nicole; Nunes-Alves, Ariane; Kreikemeyer, Bernd; Schindelin, Hermann; et al. (Frontiers in Microbiology, 2022)

PEtab-Interoperable specification of parameter estimation problems in systems biology. - Schmiester, L.; Schalte, Y.; Bergmann, F. T.; Camba, T.; Dudkin, E.; Egert, J.; Frohlich, F.; Fuhrmann, L.; Hauber, A. L.; Kemmer, S.; Lakrisenko, P.; Loos, C.; et al. (PLoS Comput Biol, 2021)
Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been-so far-no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies.
Keywords: Algorithms; Databases, Factual; Models, Biological; Models, Statistical; *Programming Languages; Reproducibility of Results; Systems Biology/*methods

Improving the FAIRness of Health Studies in Germany: The German Central Health Study Hub COVID-19. - Darms, J.; Henke, J.; Hu, X.; Schmidt, C. O.; Golebiewski, M.; Fluck, J. (Stud Health Technol Inform, 2021)
The German Central Health Study Hub COVID-19 is an online service that offers bundled access to COVID-19 related studies conducted in Germany. It combines metadata and other information of epidemiologic, public health and clinical studies into a single data repository for FAIR data access. In addition to study characteristics the system also allows easy access to study documents, as well as instruments for data collection. Study metadata and survey instruments are decomposed into individual data items and semantically enriched to ease the findability. Data from existing clinical trial registries (DRKS, clinicaltrails.gov and WHO ICTRP) are merged with epidemiological and public health studies manually collected and entered. More than 850 studies are listed as of September 2021.
Keywords: *COVID-19; Germany; Humans; Metadata; SARS-CoV-2; Surveys and Questionnaires

Specifications of standards in systems and synthetic biology: status and developments in 2021. - Schreiber, F.; Gleeson, P.; Golebiewski, M.; Gorochowski, T. E.; Hucka, M.; Keating, S. M.; Konig, M.; Myers, C. J.; Nickerson, D. P.; Sommer, B.; Waltemath, D. (J Integr Bioinform, 2021)
This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COMBINE standards in systems and synthetic biology. The 2021 special issue presents four updates of standards: Synthetic Biology Open Language Visual Version 2.3, Synthetic Biology Open Language Visual Version 3.0, Simulation Experiment Description Markup Language Level 1 Version 4, and OMEX Metadata specification Version 1.2. This document can also be consulted to identify the latest specifications of all COMBINE standards.
Keywords: *Computational Biology; Computer Simulation; Metadata; Programming Languages; Software; *Synthetic Biology

Thermodynamics of Сlassical Schwarzschild Black Holes - Maltsev, Kiril (Astronomy Reports, 2021)

Mechanical force can enhance c-Src kinase activity by impairing autoinhibition. - Daday, C.; de Buhr, S.; Mercadante, D.; Grater, F. (Biophys J, 2022)
Cellular mechanosensing is pivotal for virtually all biological processes, and many molecular mechano-sensors and their way of function are being uncovered. In this work, we suggest that c-Src kinase acts as a direct mechano-sensor. c-Src is responsible for, among others, cell proliferation, and shows increased activity in stretched cells. In its native state, c-Src has little basal activity, because its kinase domain binds to an SH2 and SH3 domain. However, it is known that c-Src can bind to p130Cas, through which force can be transmitted to the membrane. Using molecular dynamics simulations, we show that force acting between the membrane-bound N-terminus of the SH3 domain and p130Cas induces partial SH3 unfolding, thereby impeding rebinding of the kinase domain onto SH2/SH3 and effectively enhancing kinase activity. Forces involved in this process are slightly lower or similar to the forces required to pull out c-Src from the membrane through the myristoyl linker, and key interactions involved in this anchoring are salt bridges between negative lipids and nearby basic residues in c-Src. Thus, c-Src appears to be a candidate for an intriguing mechanosensing mechanism of impaired kinase inhibition, which can be potentially tuned by membrane composition and other environmental factors.
Keywords: CSK Tyrosine-Protein Kinase; Phosphorylation; *Protein-Tyrosine Kinases/metabolism; *src Homology Domains

Accurate Free Energies for Complex Condensed-Phase Reactions Using an Artificial Neural Network Corrected DFTB/MM Methodology. - Gomez-Flores, C. L.; Maag, D.; Kansari, M.; Vuong, V. Q.; Irle, S.; Grater, F.; Kubar, T.; Elstner, M. (J Chem Theory Comput, 2022)
Semiempirical methods like density functional tight-binding (DFTB) allow extensive phase space sampling, making it possible to generate free energy surfaces of complex reactions in condensed-phase environments. Such a high efficiency often comes at the cost of reduced accuracy, which may be improved by developing a specific reaction parametrization (SRP) for the particular molecular system. Thiol-disulfide exchange is a nucleophilic substitution reaction that occurs in a large class of proteins. Its proper description requires a high-level ab initio method, while DFT-GAA and hybrid functionals were shown to be inadequate, and so is DFTB due to its DFT-GGA descent. We develop an SRP for thiol-disulfide exchange based on an artificial neural network (ANN) implementation in the DFTB+ software and compare its performance to that of a standard SRP approach applied to DFTB. As an application, we use both new DFTB-SRP as components of a QM/MM scheme to investigate thiol-disulfide exchange in two molecular complexes: a solvated model system and a blood protein. Demonstrating the strengths of the methodology, highly accurate free energy surfaces are generated at a low cost, as the augmentation of DFTB with an ANN only adds a small computational overhead.

The maximum volume of hyperbolic polyhedra - Belletti, Giulio (Trans. Amer. Math. Soc., 2021)

Generalizing Stretch Lines for Surfaces with Boundary - Alessandrini, Daniele; DiSarlo, Valentina (International Mathematics Research Notices, 2021)

Large-scale geometry of the saddle connection graph - DiSarlo, Valentina; Pan, Huiping; Randecker, Anja; Tang, Robert (Trans. Amer. Math. Soc., 2021)

Borel and Volume Classes for Dense Representations of Discrete Groups - Farre, James (International Mathematics Research Notices, 2021)