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. 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. Availability and implementation: The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST.

The minimum information about a molecular interaction CAusal STatement (MI2CAST) / Toure, V; Vercruysse, S; Acencio, Ml; Lovering, Rc; Orchard, S; Bradley, G; Casals-Casas, C; Chaouiya, C; del-Toro, N; Flobak, A; Gaudet, P; Hermjakob, H; Hoyt, Ct; Licata, L; Laegreid, A; Mungall, Cj; Niknejad, A; Panni, S; Perfetto, L; Porras, P; Pratt, D; Saez-Rodriguez, J; Thieffry, D; Thomas, Pd; Turei, D; Kuiper, M. - In: BIOINFORMATICS. - ISSN 1367-4803. - 36:24(2020), pp. 5712-5718. [10.1093/bioinformatics/btaa622]

The minimum information about a molecular interaction CAusal STatement (MI2CAST)

Perfetto L;
2020

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. 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. Availability and implementation: The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST.
2020
MI2CAST, Causal interactions, Data curation, standard
01 Pubblicazione su rivista::01a Articolo in rivista
The minimum information about a molecular interaction CAusal STatement (MI2CAST) / Toure, V; Vercruysse, S; Acencio, Ml; Lovering, Rc; Orchard, S; Bradley, G; Casals-Casas, C; Chaouiya, C; del-Toro, N; Flobak, A; Gaudet, P; Hermjakob, H; Hoyt, Ct; Licata, L; Laegreid, A; Mungall, Cj; Niknejad, A; Panni, S; Perfetto, L; Porras, P; Pratt, D; Saez-Rodriguez, J; Thieffry, D; Thomas, Pd; Turei, D; Kuiper, M. - In: BIOINFORMATICS. - ISSN 1367-4803. - 36:24(2020), pp. 5712-5718. [10.1093/bioinformatics/btaa622]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1660168
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