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The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST).

Authors :
Touré V
Vercruysse S
Acencio ML
Lovering RC
Orchard S
Bradley G
Casals-Casas C
Chaouiya C
Del-Toro N
Flobak Å
Gaudet P
Hermjakob H
Hoyt CT
Licata L
Lægreid A
Mungall CJ
Niknejad A
Panni S
Perfetto L
Porras P
Pratt D
Saez-Rodriguez J
Thieffry D
Thomas PD
Türei D
Kuiper M
Source :
Bioinformatics (Oxford, England) [Bioinformatics] 2021 Apr 05; Vol. 36 (24), pp. 5712-5718.
Publication Year :
2021

Abstract

Motivation: A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources.<br />Results: Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources.<br />Availability and Implementation: The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST.<br />Supplementary Information: Supplementary data are available at Bioinformatics online.<br /> (© The Author(s) 2020. Published by Oxford University Press.)

Subjects

Subjects :
Causality
Humans
Software

Details

Language :
English
ISSN :
1367-4811
Volume :
36
Issue :
24
Database :
MEDLINE
Journal :
Bioinformatics (Oxford, England)
Publication Type :
Academic Journal
Accession number :
32637990
Full Text :
https://doi.org/10.1093/bioinformatics/btaa622