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53 Publications visible to you, out of a total of 53
Bioschemas Resource Index for Chem and Plants

Abstract (Expand)

As part of the BioHackathon Europe 2023, we here report on the progress of the hacking team preparing a resource index and knowledge graph based on the JSON-LD Bioschemas markup from several resources …al resources in the life- and natural sciences, predominantly from the fields of plant- and (bio)chemistry research. This preliminary analysis will allow us to better understand how Bioschemas markup is currently used in these two communities, so we can take actions to improve guidelines and validation on the Bioschemas markup and the data providers side. The lessons learnt will be useful for other communities as well. The ultimate goal is facilitating and improving interoperability across resources.

Authors: Daniel Arend, Alessio Del Conte, Manuel Feser, Yojana Gadiya, Alban Gaignard, Leyla Jael Castro, Ivan Mičetić, Sebastien Moretti, Steffen Neumann, Noura Rayya, Ginger Tsueng, Egon Willighagen, Ulrike Wittig

Date Published: 30th Jan 2024

Publication Type: Misc

A research data management (RDM) community for ELIXIR

Abstract (Expand)

Research data management (RDM) is central to the implementation of the FAIR (Findable Accessible, Interoperable, Reusable) and Open Science principles. Recognising the importance of RDM, ELIXIR Platforms …IXIR Platforms and Nodes have invested in RDM and launched various projects and initiatives to ensure good data management practices for scientific excellence. These projects have resulted in a rich set of tools and resources highly valuable for FAIR data management. However, these resources remain scattered across projects and ELIXIR structures, making their dissemination and application challenging. Therefore, it becomes imminent to coordinate these efforts for sustainable and harmonised RDM practices with dedicated forums for RDM professionals to exchange knowledge and share resources. The proposed ELIXIR RDM Community will bring together RDM experts to develop ELIXIR’s vision and coordinate its activities, taking advantage of the available assets. It aims to coordinate RDM best practices and illustrate how to use the existing ELIXIR RDM services. The Community will be built around three integral pillars, namely, a network of RDM professionals, RDM knowledge management and RDM training expertise and resources. It will also engage with external stakeholders to leverage benefits and provide a forum to RDM professionals for regular knowledge exchange, capacity building and development of harmonised RDM practices, keeping in line with the overall scope of the RDM Community. In the short term, the Community aims to build upon the existing resources and ensure that the content of these remain up to date and fit for purpose. In the long run, the Community will aim to strengthen the skills and knowledge of its RDM professionals to support the emerging needs of the scientific community. The Community will also devise an effective strategy to engage with other ELIXIR structures and international stakeholders to influence and align with developments and solutions in the RDM field.

Authors: Flora D'Anna, Niclas Jareborg, Mijke Jetten, Minna Ahokas, Pinar Alper, Robert Andrews, Korbinian Bösl, Teresa D’Altri, Daniel Faria, Nazeefa Fatima, Siiri Fuchs, Clare Garrard, Wei Gu, Katharina F. Heil, Yvonne Kallberg, Flavio Licciulli, Nils-Christian Lübke, Ana M. P. Melo, Ivan Mičetić, Jorge Oliveira, Anastasis Oulas, Patricia M. Palagi, Krzysztof Poterlowicz, Xenia Perez-Sitja, Patrick Ruch, Susanna-Assunta Sansone, Helena Schnitzer, Celia van Gelder, Thanasis Vergoulis, Daniel Wibberg, Ulrike Wittig, Brane Leskošek, Jiri Vondrasek, Munazah Andrabi

Date Published: 2024

Publication Type: Journal

High-Throughput Phenotypic Screening and Machine Learning Methods Enabled the Selection of Broad-Spectrum Low-Toxicity Antitrypanosomatidic Agents.

Abstract (Expand)

Broad-spectrum anti-infective chemotherapy agents with activity against Trypanosomes, Leishmania, and Mycobacterium tuberculosis species were identified from a high-throughput phenotypic screening … program of the 456 compounds belonging to the Ty-Box, an in-house industry database. Compound characterization using machine learning approaches enabled the identification and synthesis of 44 compounds with broad-spectrum antiparasitic activity and minimal toxicity against Trypanosoma brucei, Leishmania Infantum, and Trypanosoma cruzi. In vitro studies confirmed the predictive models identified in compound 40 which emerged as a new lead, featured by an innovative N-(5-pyrimidinyl)benzenesulfonamide scaffold and promising low micromolar activity against two parasites and low toxicity. Given the volume and complexity of data generated by the diverse high-throughput screening assays performed on the compounds of the Ty-Box library, the chemoinformatic and machine learning tools enabled the selection of compounds eligible for further evaluation of their biological and toxicological activities and aided in the decision-making process toward the design and optimization of the identified lead.

Authors: P. Linciano, A. Quotadamo, R. Luciani, M. Santucci, K. M. Zorn, D. H. Foil, T. R. Lane, A. Cordeiro da Silva, N. Santarem, C. B Moraes, L. Freitas-Junior, U. Wittig, W. Mueller, M. Tonelli, S. Ferrari, A. Venturelli, S. Gul, M. Kuzikov, B. Ellinger, J. Reinshagen, S. Ekins, M. P. Costi

Date Published: 3rd Nov 2023

Publication Type: Journal

Improved insights into the SABIO-RK database via visualization.

Abstract (Expand)

SABIO-RK is a database for biochemical reactions and their kinetics. Data in SABIO-RK are inherently multidimensional and complex. The complex relationships between the data are often difficult to … follow or even not represented when using standard tabular views. With an increasing number of data points the mismatch between tables and insights becomes more obvious, and getting an overview of the data becomes harder. Such complex data benefit from being presented using specially adapted visual tools. Visualization is a natural and user-friendly way to quickly get an overview of the data and to detect clusters and outliers. Here, we describe the implementation of a variety of visualization concepts into a common interface within the SABIO-RK biochemical reaction kinetics database. For that purpose, we use a heat map, parallel coordinates and scatter plots to allow the interactive visual exploration of general entry-based information of biochemical reactions and specific kinetic parameter values. Database URL https://sabiork.h-its.org/.

Authors: D. Dudas, U. Wittig, M. Rey, A. Weidemann, W. Muller

Date Published: 31st Mar 2023

Publication Type: Journal

ReStoRunT: Simple Recording, Storing, Running and Tracing changes in Spreadsheets

Abstract (Expand)

In addition to the ubiquitous big data, one key challenge indata processing and management in the life sciences is the diversity ofsmall data. Diverse pieces of small data have to be transformed … intostandards-compliant data. Here, the challenge lies not in the difficulty ofsingle steps that need to be performed, but rather in the fact that manytransformation tasks are to be performed once or only a few times. Thislimits the time that can be put into automated approaches, which inturn severely limits the verifiability of such transformations.As much of the data to be processed is stored in spreadsheets, withinthis paper we justify and propose a lightweight recording-based solutionthat works on a wide variety of spreadsheet programs, from MicrosoftExcel to Google Docs.

Authors: Wolfgang Müller, Lukrecia Mertova

Date Published: 23rd Feb 2023

Publication Type: Journal

EnzymeML: seamless data flow and modeling of enzymatic data.

Abstract (Expand)

The design of biocatalytic reaction systems is highly complex owing to the dependency of the estimated kinetic parameters on the enzyme, the reaction conditions, and the modeling method. Consequently, … reproducibility of enzymatic experiments and reusability of enzymatic data are challenging. We developed the XML-based markup language EnzymeML to enable storage and exchange of enzymatic data such as reaction conditions, the time course of the substrate and the product, kinetic parameters and the kinetic model, thus making enzymatic data findable, accessible, interoperable and reusable (FAIR). The feasibility and usefulness of the EnzymeML toolbox is demonstrated in six scenarios, for which data and metadata of different enzymatic reactions are collected and analyzed. EnzymeML serves as a seamless communication channel between experimental platforms, electronic lab notebooks, tools for modeling of enzyme kinetics, publication platforms and enzymatic reaction databases. EnzymeML is open and transparent, and invites the community to contribute. All documents and codes are freely available at https://enzymeml.org .

Authors: S. Lauterbach, H. Dienhart, J. Range, S. Malzacher, J. D. Sporing, D. Rother, M. F. Pinto, P. Martins, C. E. Lagerman, A. S. Bommarius, A. V. Host, J. M. Woodley, S. Ngubane, T. Kudanga, F. T. Bergmann, J. M. Rohwer, D. Iglezakis, A. Weidemann, U. Wittig, C. Kettner, N. Swainston, S. Schnell, J. Pleiss

Date Published: 9th Feb 2023

Publication Type: Journal

Systems Biology in ELIXIR: modelling in the spotlight.

Abstract (Expand)

In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems … biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR's future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives.

Authors: V. Martins Dos Santos, M. Anton, B. Szomolay, M. Ostaszewski, I. Arts, R. Benfeitas, V. Dominguez Del Angel, E. Dominguez-Romero, P. Ferk, D. Fey, C. Goble, M. Golebiewski, K. Gruden, K. F. Heil, H. Hermjakob, P. Kahlem, M. I. Klapa, J. Koehorst, A. Kolodkin, M. Kutmon, B. Leskosek, S. Moretti, W. Muller, M. Pagni, T. Rezen, M. Rocha, D. Rozman, D. Safranek, W. T Scott, R. S. M. Sheriff, M. Suarez Diez, K. Van Steen, H. V. Westerhoff, U. Wittig, K. Wolstencroft, A. Zupanic, C. T. Evelo, J. M. Hancock

Date Published: 8th Feb 2023

Publication Type: Journal

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