TY - JOUR
T1 - BioKC
T2 - a collaborative platform for curation and annotation of molecular interactions
AU - Vega, Carlos
AU - Ostaszewski, Marek
AU - Grouès, Valentin
AU - Schneider, Reinhard
AU - Satagopam, Venkata
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/3/27
Y1 - 2024/3/27
N2 - Curation of biomedical knowledge into systems biology diagrammatic or computational models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever-increasing growth of domain literature. New findings demonstrating elaborate relationships between multiple molecules, pathways and cells have to be represented in a format suitable for systems biology applications. Importantly, curation should capture the complexity of molecular interactions in such a format together with annotations of the involved elements and support stable identifiers and versioning. This challenge calls for novel collaborative tools and platforms allowing to improve the quality and the output of the curation process. In particular, community-based curation, an important source of curated knowledge, requires support in role management, reviewing features and versioning. Here, we present Biological Knowledge Curation (BioKC), a web-based collaborative platform for the cura-tion and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML). BioKC offers a graphical user interface for curation of complex molecular interactions and their annotation with stable identifiers and supporting sentences. With the support of collaborative curation and review, it allows to construct building blocks for systems biol-ogy diagrams and computational models. These building blocks can be published under stable identifiers and versioned and used as annotations, supporting knowledge building for modelling activities.
AB - Curation of biomedical knowledge into systems biology diagrammatic or computational models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever-increasing growth of domain literature. New findings demonstrating elaborate relationships between multiple molecules, pathways and cells have to be represented in a format suitable for systems biology applications. Importantly, curation should capture the complexity of molecular interactions in such a format together with annotations of the involved elements and support stable identifiers and versioning. This challenge calls for novel collaborative tools and platforms allowing to improve the quality and the output of the curation process. In particular, community-based curation, an important source of curated knowledge, requires support in role management, reviewing features and versioning. Here, we present Biological Knowledge Curation (BioKC), a web-based collaborative platform for the cura-tion and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML). BioKC offers a graphical user interface for curation of complex molecular interactions and their annotation with stable identifiers and supporting sentences. With the support of collaborative curation and review, it allows to construct building blocks for systems biol-ogy diagrams and computational models. These building blocks can be published under stable identifiers and versioned and used as annotations, supporting knowledge building for modelling activities.
UR - http://www.scopus.com/inward/record.url?scp=85189281215&partnerID=8YFLogxK
UR - https://pubmed.ncbi.nlm.nih.gov/38537198
U2 - 10.1093/database/baae013
DO - 10.1093/database/baae013
M3 - Article
C2 - 38537198
AN - SCOPUS:85189281215
SN - 1758-0463
VL - 2024
JO - Database : the journal of biological databases and curation
JF - Database : the journal of biological databases and curation
ER -