CausalTab: PSI-MITAB 2.8 updated format for signaling data representation and dissemination
Livia PerfettoiD, Márcio Luís AcencioiD, Glyn Bradley, Gianni CesareniiD, Noemí del‐ToroiD, Dávid FazekasiD, Henning HermjakobiD, Tamas Douglas KorcsmarosiD, Martin T. R. KuiperiD, Astrid LægreidiD, Prisca Lo SurdoiD, Ruth C. LoveringiD, Sandra E. OrchardiD, Pablo PorrasiD, Paul D. ThomasiD, Vasundra TouréiD, John ZobolasiD, Luana LicataiD
Abstract
Combining multiple layers of information underlying biological complexity into a structured framework, and in particular deciphering the molecular mechanisms behind cellular phenotypes, represent two challenges in systems biology. A key task is the formalisation of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signaling information, such as SIGNOR, SignaLink and IntAct, focus on capturing, organising and displaying signaling 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, through the development of a standardized exchange format, ontologies and controlled vocabularies supporting the domain of causal interactions. 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 signaling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated MITAB2.8. 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 signaling networks more precisely and with higher coverage than before.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 32
- FWCI
- 2.07
- Field percentile
- top 12%
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Inter-Tools: a toolkit for interactome analysis
Hannah Beth Catabia, Caren Smith, José María Ordovás·bioRxiv·Jun 15, 2017
- Can we assume the gene expression profile as a proxy for signaling network activity?
Mehran Piran, Reza Karbalaei, … Mohieddin Jafari·BiomoleculesPeer-reviewed·Jun 3, 2020
- Understanding signaling and metabolic paths using semantified and harmonized information about biological interactions
Ryan A. Miller, Martina Kutmon, … Egon Willighagen·PLoS ONEPeer-reviewed·Apr 18, 2022
- The strength of protein-protein interactions controls the information capacity and dynamical response of signaling networks
Ching-Hao Wang, Pankaj Mehta, Caleb J. Bashor·bioRxiv·Nov 23, 2018
- PSINDB: A comprehensive database of postsynaptic protein-protein interactions
Zsófia E. Kálmán, Dániel Dudola, … László Dobson·bioRxiv·Jul 19, 2021
- Stop Bickering! Reconciling Signaling Pathway Databases with Network Topologies
Tobias Rubel, Pramesh Singh, Anna Ritz·bioRxiv·Aug 3, 2021