Gudrun Gygli project_administratorasset_housekeeperasset_gatekeeperprogramme_administrator

Projects: Simulation Foundries, CML for thermophysical properties of mixtures, Test Project (dummy), Towards Reproducible Enzyme Modeling

Institutions: University of Stuttgart, Karlsruhe Institute of Technology (KIT)

https://orcid.org/0000-0001-9119-1778
Mihaly Koltai project_administrator

Projects: CausalDB, Colosys

Institutions: Institut Curie

https://orcid.org/0000-0002-7341-5114
John Zobolas

Projects: NTNU Health Druglogics, Colosys

Institutions: Norwegian University of Science and Technology

https://orcid.org/0000-0002-3609-8674
Maja Zagorscak project_administratorasset_housekeeperasset_gatekeeperprogramme_administrator

Projects: pISA-tree, HYp - Spatiotemporal analysis of hypersensitive response to Potato virus Y in potato, INDIE - Biotechnological production of sustainable indole, _p_stRT, ADAPT - Accelerated Development of multiple-stress tolerAnt PoTato, tst, tst2

Institutions: National Institute of Biology, tst

https://orcid.org/0000-0002-1669-6482
Niko Beerenwinkel

Projects: SysVirDrug

Institutions: ETH Zurich

https://orcid.org/0000-0002-0573-6119
Steven Watterson

Projects: HUMET Startup, COVID-19 Disease Map

Institutions: University of Ulster

https://orcid.org/0000-0002-2750-6410
Lars Malmstroem

Projects: FAIRDOM

Institutions: University of Zürich

https://orcid.org/0000-0001-9885-9312
Yuriy Orlov

Projects: ZucAt

Institutions: Institute of Cytology and Genetics, Novosibirsk State University

Matthias König project_administratorasset_housekeeperasset_gatekeeper

Projects: Kinetics on the move - Workshop 2016, Multi-Scale Models for Personalized Liver Function Tests (LiSyM-MM-PLF), FAIRDOM user meeting, COMBINE Multicellular Modelling, FAIRDOM & LiSyM & de.NBI Data Structuring Training

Institutions: Charité University Medicine Berlin, Humboldt-Universität zu Berlin, Humboldt University Berlin

https://orcid.org/0000-0003-1725-179X
Michael Holcombe

Projects: SUMO

Institutions: University of Sheffield

Harmonizing semantic annotations for computational models in biology
FAIRDOM, LiSyM Core Infrastructure and Management (LiSyM-PD), COMBINE Multicellular Modelling, GMDS Project Group "FAIRe Dateninfrastrukturen für die Biomedizinische Informatik", COVID-19 Disease Map

Abstract (Expand)

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability … and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Authors: Maxwell Lewis Neal, Matthias König, David Nickerson, Göksel Mısırlı, Reza Kalbasi, Andreas Dräger, Koray Atalag, Vijayalakshmi Chelliah, Michael T Cooling, Daniel L Cook, Sharon Crook, Miguel de Alba, Samuel H Friedman, Alan Garny, John H Gennari, Padraig Gleeson, Martin Golebiewski, Michael Hucka, Nick Juty, Chris Myers, Brett G Olivier, Herbert M Sauro, Martin Scharm, Jacky L Snoep, Vasundra Touré, Anil Wipat, Olaf Wolkenhauer, Dagmar Waltemath

Date Published: 1st Mar 2019

Publication Type: Journal

Data Formats for Systems Biology and Quantitative Modeling
FAIRDOM, LiSyM Core Infrastructure and Management (LiSyM-PD), COMBINE Multicellular Modelling, COVID-19 Disease Map

Abstract (Expand)

Data standards support the reliable exchange of information, the interoperability of tools, and the reproducibility of scientific results. In systems biology standards are agreed ways of structuring, … describing, and associating models and data, as well as their respective parts, graphical visualization, and information about applied experimental or computational methods. Such standards also assist with describing how constituent parts interact together, or are linked, and how they are embedded in their environmental and experimental context. Here the focus will be on standards for formatting models and their content, and on metadata checklists and ontologies that support modeling.

Author: Martin Golebiewski

Date Published: 2019

Publication Type: InBook

Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices.
FAIRDOM, LiSyM Core Infrastructure and Management (LiSyM-PD), COMBINE Multicellular Modelling, COVID-19 Disease Map

Abstract (Expand)

Computational systems biology involves integrating heterogeneous datasets in order to generate models. These models can assist with understanding and prediction of biological phenomena. Generating … datasets and integrating them into models involves a wide range of scientific expertise. As a result these datasets are often collected by one set of researchers, and exchanged with others researchers for constructing the models. For this process to run smoothly the data and models must be FAIR-findable, accessible, interoperable, and reusable. In order for data and models to be FAIR they must be structured in consistent and predictable ways, and described sufficiently for other researchers to understand them. Furthermore, these data and models must be shared with other researchers, with appropriately controlled sharing permissions, before and after publication. In this chapter we explore the different data and model standards that assist with structuring, describing, and sharing. We also highlight the popular standards and sharing databases within computational systems biology.

Authors: N. J. Stanford, M. Scharm, P. D. Dobson, M. Golebiewski, M. Hucka, V. B. Kothamachu, D. Nickerson, S. Owen, J. Pahle, U. Wittig, D. Waltemath, C. Goble, P. Mendes, J. Snoep

Date Published: 12th Oct 2019

Publication Type: Journal

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