The first 10 years of the international coordination network for standards in systems and synthetic biology (COMBINE)

Abstract (Expand)

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together … researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

Authors: Dagmar Waltemath, Martin Golebiewski, Michael L Blinov, Padraig Gleeson, Henning Hermjakob, Michael Hucka, Esther Thea Inau, Sarah M Keating, Matthias König, Olga Krebs, Rahuman S Malik-Sheriff, David Nickerson, Ernst Oberortner, Herbert M Sauro, Falk Schreiber, Lucian Smith, Melanie I Stefan, Ulrike Wittig, Chris J Myers

Date Published: 24th Aug 2020

Publication Type: Journal

Ten Simple Rules for FAIR Sharing of Experimental and Clinical Data with the Modeling Community

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Science continues to become more interdisciplinary and to involve increasingly complex data sets. Many projects in the biomedical and health-related sciences follow or aim to follow the principles of …rinciples of FAIR data sharing, which has been demonstrated to foster collaboration, to lead to better research outcomes, and to help ensure reproducibility of results. Data generated in the course of biomedical and health research present specific challenges for FAIR sharing in the sense that they are heterogeneous and highly sensitive to context and the needs of protection and privacy. Data sharing must respect these features without impeding timely dissemination of results, so that they can contribute to time-critical advances in medical therapy and treatment. Modeling and simulation of biomedical processes have become established tools, and a global community has been developing algorithms, methodologies, and standards for applying biomedical simulation models in clinical research. However, it can be difficult for clinician scientists to follow the specific rules and recommendations for FAIR data sharing within this domain. We seek to clarify the standard workflow for sharing experimental and clinical data with the simulation modeling community. By following these recommendations, data sharing will be improved, collaborations will become more effective, and the FAIR publication and subsequent reuse of data will become possible at the level of quality necessary to support biomedical and health-related sciences.

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: 19th Nov 2021

Publication Type: Journal

Proceedings of the 10th Computational Modeling in Biology Network (COMBINE) Meeting 2019

Abstract (Expand)

These are the conference proceedings of COMBINE 2019, the 10th Computational Modeling in Biology Network (COMBINE) meeting that took place in Heidelberg (Germany) from July 15th to July 19th, 2019. The …e Computational Modeling in Biology Network (COMBINE) is an initiative to coordinate the development of the various community standards and formats for computational models in the life sciences. It was created in 2010 to enable the sharing of resources, tools, and other infrastructure, and to coordinate standardization efforts for modeling in biology. COMBINE brings standard communities together around activities that are mutually beneficial. These activities include making specification documents available from a common location, providing a central point of contact, and organizing regular face-to-face meetings. To this end, the COMBINE network organizes an annual conference style meeting (the COMBINE Forum) and annual hackathon style events called HARMONY (Hackathon on Resources for Modeling in Biology), as well as tutorials and training events. At COMBINE 2019 a combination of keynote lectures, invited talks and interactive breakout discussions, as well as contributed talks, posters and lightning talks, selected from submitted abstracts, provided the basis for the meeting, offering diverse formats to exchange information, to discuss and work on interoperability problems and to demonstrate support for standards implemented in modelling tools, platforms and databases. One special focus of COMBINE 2019 was on the standardization need in systems medicine, which has been recognized as a necessity for computer-assisted personalized medicine. To direct attention to this topic, the European standardization framework for data integration and data-driven in silico models (EUSTANDS4PM) organized a workshop as part of COMBINE 2019. Also, reproducibility in modelling was a main topic, as reflected by several sessions and workshops. Besides these focus themes, also sessions, workshops and breakout discussions around single standards, their further development and their interoperability helped to advance the standardization, standing in the tradition of COMBINE.

Authors: Martin Golebiewski, Dagmar Waltemath

Date Published: 15th Jul 2019

Publication Type: Proceedings

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