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Distanzbasierte Inferenz von Genbäumen unter Berücksichtigung ihres Speziesbaumes

Abstract (Expand)

In dieser Arbeit wird Spearfish, eine neue Methode zur distanzbasierten Inferenz von Genbäumen, entwickelt und getestet. Spearfish verwendet die paarweisen Distanzen der Gensequenzen, sowie die Distanzen … der zugehörigen Spezies im Speziesbaum, in einem Clustering-Verfahren, um 10 Genbäume zu rekonstruieren. Der beste wird anschließend mithilfe eines statistischen Evaluierungsverfahrens ausgewählt. Auf allen getesteten simulierten Datensätzen konnte gezeigt werden, dass die von Spearfish inferierten Bäume durchschnittlich eine Distanz von 0,213 zum echten Genbaum besitzen. Damit ist es 2,18-mal genauer als Methoden wie RAxML-NG, welche den Speziesbaum nicht berücksichtigen. Spearfish ist 25,85% ungenauer, aber 49,63% schneller als GeneRax, eine der führenden Methoden, die Genbäume mithilfe ihres Speziesbaumes korrigieren. So kann Spearfish verwendet werden, um Startbäume für GeneRax zu rekonstruieren oder bei goßen Datensätzen sogar zu ersetzen.

Authors: Lukas Knirsch, Benoit Morel, Alexandros Stamatakis

Date Published: 2nd Oct 2025

Publication Type: Bachelor's Thesis

BioHackEU24 report: Creating user benefit from ARC-ISA RO-Crate machine-actionability & Increasing FAIRness of digital agrosystem resources by extending Bioschemas

Abstract (Expand)

As part of the BioHackathon Europe 2024, we here report on the progress that both project 19 and project 24 have made during the event. For the purpose of this report we will present the abstract of … abstract of both projects and then dive deeper on what work was done during the BioHackathon.

Authors: Sebastian Beier, Daniel Arend, Daniel Bauer, Marco Brandizi, Dominik Brilhaus, Eli Chadwick, Vera Clemens, Michael Robin Crusoe, Manuel Feser, Jonas Grieb, Xiaoming Hu, Abigail Miller, Timo Mühlhaus, Stuart Owen, Maja Rey, Gabriel Schneider, Julian Schneider, Kevin Schneider, Heinrich Lukas Weil, Florian Wetzels

Date Published: 2nd Feb 2025

Publication Type: Tech report

Hot Jupiter engulfment by an early red giant in 3D hydrodynamics

Abstract (Expand)

Hot Jupiters are gas giant planets with orbital periods of a few days and are found in 0.1–1% of Sun-like stars. They are expected to be engulfed during their host star’s radial expansion on the red … giant branch, which may account for observed rapidly rotating and chemically enriched giant stars. We performed 3D hydrodynamical simulations of hot Jupiter engulfment by a 1 M⊙, 4 R⊙ early red giant. Our ‘global’ simulations simultaneously resolve the stellar envelope and planetary structure, modelling the hot Jupiter as a polytropic gas sphere. The hot Jupiter spirals in due to ram-pressure drag. A substantial fraction of its mass is continuously ablated in this process, although the mass-loss rate is resolution dependent. We estimate that this could enhance the surface lithium abundance by up to ≈0.1 dex. The hot Jupiter is disrupted by a combination of ram pressure and tidal forces near the base of the convective envelope, with the deepest material penetrating to the radiative zone. The star experiences modest spin-up (∼1 km s−1), and engulfing a more massive companion may be required to produce a rapidly rotating giant. Drag heating near the surface and hydrogen recombination in the small amount of unbound ejecta recorded in the simulation could power an optical transient, although this needs to be confirmed by a calculation that has adequate resolution at the stellar surface.

Authors: Mike Y. M. Lau, Matteo Cantiello, Adam S. Jermyn, Morgan MacLeod, Ilya Mandel, Daniel J. Price

Date Published: 1st Feb 2025

Publication Type: Journal

The Lunar Gravitational-wave Antenna: mission studies and science case

Abstract

Not specified

Authors: Parameswaran Ajith, Pau Amaro Seoane, Manuel Arca Sedda, Riccardo Arcodia, Francesca Badaracco, Biswajit Banerjee, Enis Belgacem, Giovanni Benetti, Stefano Benetti, Alexey Bobrick, Alessandro Bonforte, Elisa Bortolas, Valentina Braito, Marica Branchesi, Adam Burrows, Enrico Cappellaro, Roberto Della Ceca, Chandrachur Chakraborty, Shreevathsa Chalathadka Subrahmanya, Michael W. Coughlin, Stefano Covino, Andrea Derdzinski, Aayushi Doshi, Maurizio Falanga, Stefano Foffa, Alessia Franchini, Alessandro Frigeri, Yoshifumi Futaana, Oliver Gerberding, Kiranjyot Gill, Matteo Di Giovanni, Ines Francesca Giudice, Margherita Giustini, Philipp Gläser, Jan Harms, Joris van Heijningen, Francesco Iacovelli, Bradley J. Kavanagh, Taichi Kawamura, Arun Kenath, Elisabeth-Adelheid Keppler, Chiaki Kobayashi, Goro Komatsu, Valeriya Korol, N. V. Krishnendu, Prayush Kumar, Francesco Longo, Michele Maggiore, Michele Mancarella, Andrea Maselli, Alessandra Mastrobuono-Battisti, Francesco Mazzarini, Andrea Melandri, Daniele Melini, Sabrina Menina, Giovanni Miniutti, Deeshani Mitra, Javier Morán-Fraile, Suvodip Mukherjee, Niccolò Muttoni, Marco Olivieri, Francesca Onori, Maria Alessandra Papa, Ferdinando Patat, Andrea Perali, Tsvi Piran, Silvia Piranomonte, Alberto Roper Pol, Masroor C. Pookkillath, R. Prasad, Vaishak Prasad, Alessandra De Rosa, Sourav Roy Chowdhury, Roberto Serafinelli, Alberto Sesana, Paola Severgnini, Angela Stallone, Jacopo Tissino, Hrvoje Tkalčić, Lina Tomasella, Martina Toscani, David Vartanyan, Cristian Vignali, Lucia Zaccarelli, Morgane Zeoli, Luciano Zuccarello

Date Published: 28th Jan 2025

Publication Type: Journal

Predicting hydrogen atom transfer energy barriers using Gaussian process regression

Abstract

Not specified

Authors: Evgeni Ulanov, Ghulam A. Qadir, Kai Riedmiller, Pascal Friederich, Frauke Gräter

Date Published: 10th Jan 2025

Publication Type: Journal

Comparative evaluation of standard machine learning models for liver fibrosis detection

Abstract

Not specified

Authors: Marcus Buchwald, Pascal Memmesheimer, Arash Dooghaie Moghadam, Ines Tuschner, Laura Santamaria Suarez, Timo Itzel, Christoph Antoni, Jimmy Daza, Catharina Gerhards, Michael Neumaier, Christop Brochhausen, Peter R. Galle, Matthias Ebert, Arndt Weinmann, Jürgen Hesser, Vincent Heuveline, Andreas Teufel

Date Published: 10th Jan 2025

Publication Type: Journal

Modeling and predicting spatio-temporal dynamics of PM_2.5 concentrations through time-evolving covariance models

Abstract

Not specified

Authors: Ghulam A. Qadir, Ying Sun

Date Published: 2025

Publication Type: Journal

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