CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination

Abstract

Motivation Combining multiple layers of information underlying biological complexity into a structured framework represent a challenge in systems biology. A key task is the formalization of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signalling information, focus on capturing, organizing and displaying signalling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources.

Results Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signalling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated PSI-MITAB 2.8. We define the new term ‘causal interaction’, and related child terms, which are children of the PSI-MI ‘molecular interaction’ term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signalling networks more precisely and with higher coverage than before.

Availability and implementation PSI-MITAB 2.8 format and the new reference implementation of PSICQUIC are available online (https://psicquic.github.io/ and https://psicquic.github.io/MITAB28Format.html).

Supplementary information Supplementary data are available at Bioinformatics online.

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Additional Info

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Author Perfetto, L
Last Updated November 20, 2019, 16:52 (UTC)
Created November 4, 2019, 17:56 (UTC)
Article Host Type publisher
Article Is Open Access true
Article License Type publisher-specific, author manuscript: https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model
Article Version Type acceptedVersion
Citation Report https://scite.ai/reports/10.1093/bioinformatics/btz132
DOI 10.1093/bioinformatics/btz132
Date Last Updated 2019-11-04T17:56:02.026005
Evidence open (via crossref license, author manuscript)
Funder code(s) Associazione Italiana per la Ricerca sul Cancro (20322, 18137); Norges Forskningsråd (247727); British Heart Foundation (RG/13/5/30112); Biotechnology and Biological Sciences Research Council (BB/J004529/1, BB/P016774/1); Wellcome Trust (); ELIXIR-IIB (); Italian Node of the European ELIXIR (); Gene Regulation Ensemble Effort for the Knowledge Commons (CA15205); DEPTH Project of the European Research Council (322749); Norwegian University of Science and Technology’s Strategic Research Area ‘NTNU Health’ (); ERACoSysMed grant COLOSYS (); National Institute for Health Research University College London Hospitals Biomedical Research Centre (OTAR-044); Earlham Institute (); Quadrams Institute ()
Journal Is Open Access false
Open Access Status hybrid
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Publisher URL https://doi.org/10.1093/bioinformatics/btz132