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CausalBuilder: bringing the MI2CAST causal interaction annotation standard to the curator
Author(s) -
Vasundra Touré,
John Zobolas,
Martin Kuiper,
Steven Vercruysse
Publication year - 2020
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baaa107
Subject(s) - computer science , interface (matter) , context (archaeology) , annotation , data curation , syntax , representation (politics) , relevance (law) , user interface , statement (logic) , human–computer interaction , data science , information retrieval , artificial intelligence , programming language , bubble , maximum bubble pressure method , parallel computing , politics , political science , law , biology , paleontology
Molecular causal interactions are defined as regulatory connections between biological components. They are commonly retrieved from biological experiments and can be used for connecting biological molecules together to enable the building of regulatory computational models that represent biological systems. However, including a molecular causal interaction in a model requires assessing its relevance to that model, based on the detailed knowledge about the biomolecules, interaction type and biological context. In order to standardize the representation of this knowledge in 'causal statements', we recently developed the Minimum Information about a Molecular Interaction Causal Statement (MI2CAST) guidelines. Here, we introduce causalBuilder: an intuitive web-based curation interface for the annotation of molecular causal interactions that comply with the MI2CAST standard. The causalBuilder prototype essentially embeds the MI2CAST curation guidelines in its interface and makes its rules easy to follow by a curator. In addition, causalBuilder serves as an original application of the Visual Syntax Method general-purpose curation technology and provides both curators and tool developers with an interface that can be fully configured to allow focusing on selected MI2CAST concepts to annotate. After the information is entered, the causalBuilder prototype produces genuine causal statements that can be exported in different formats.

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