Publications

51 Publications visible to you, out of a total of 51

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: Vitor Martins dos Santos, Mihail Anton, Barbara Szomolay, Marek Ostaszewski, Ilja Arts, Rui Benfeitas, Victoria Dominguez Del Angel, Polonca Ferk, Dirk Fey, Carole Goble, Martin Golebiewski, Kristina Gruden, Katharina F. Heil, Henning Hermjakob, Pascal Kahlem, Maria I. Klapa, Jasper Koehorst, Alexey Kolodkin, Martina Kutmon, Brane Leskošek, Sébastien Moretti, Wolfgang Müller, Marco Pagni, Tadeja Rezen, Miguel Rocha, Damjana Rozman, David Šafránek, Rahuman S. Malik Sheriff, Maria Suarez Diez, Kristel Van Steen, Hans V Westerhoff, Ulrike Wittig, Katherine Wolstencroft, Anze Zupanic, Chris T. Evelo, John M. Hancock

Date Published: 2022

Publication Type: Journal

Abstract (Expand)

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.

Authors: J. Range, C. Halupczok, J. Lohmann, N. Swainston, C. Kettner, F. T. Bergmann, A. Weidemann, U. Wittig, S. Schnell, J. Pleiss

Date Published: 11th Dec 2021

Publication Type: Journal

Abstract

Not specified

Authors: Julian Matschinske, Nicolas Alcaraz, Arriel Benis, Martin Golebiewski, Dominik G. Grimm, Lukas Heumos, Tim Kacprowski, Olga Lazareva, Markus List, Zakaria Louadi, Josch K. Pauling, Nico Pfeifer, Richard Röttger, Veit Schwämmle, Gregor Sturm, Alberto Traverso, Kristel Van Steen, Martiela Vaz de Freitas, Gerda Cristal Villalba Silva, Leonard Wee, Nina K. Wenke, Massimiliano Zanin, Olga Zolotareva, Jan Baumbach, David B. Blumenthal

Date Published: 1st Oct 2021

Publication Type: Journal

Abstract (Expand)

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.

Authors: G. Mayer, W. Muller, K. Schork, J. Uszkoreit, A. Weidemann, U. Wittig, M. Rey, C. Quast, J. Felden, F. O. Glockner, M. Lange, D. Arend, S. Beier, A. Junker, U. Scholz, D. Schuler, H. A. Kestler, D. Wibberg, A. Puhler, S. Twardziok, J. Eils, R. Eils, S. Hoffmann, M. Eisenacher, M. Turewicz

Date Published: 2nd Sep 2021

Publication Type: Journal

Abstract

Not specified

Authors: Matthias König, Jan Grzegorzewski, Martin Golebiewski, Henning Hermjakob, Mike Hucka, Brett Olivier, Sarah Keating, David Nickerson, Falk Schreiber, Rahuman Sheriff, Dagmar Waltemath

Date Published: 13th Aug 2021

Publication Type: Journal

Abstract

Not specified

Authors: Mark-Christoph Müller, Sucheta Ghosh, Ulrike Wittig, Maja Rey

Date Published: 11th Jun 2021

Publication Type: InProceedings

Abstract (Expand)

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.

Authors: Maja Rey, Andreas Weidemann, Ulrike Wittig, Dorotea Dudas, Sucheta Ghosh, Martin Golebiewski, Xiaoming Hu, Wolfgang Müller

Date Published: 2021

Publication Type: Booklet

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