Reference : BioKC: a collaborative platform for systems biology model curation and annotation
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
Systems Biomedicine
http://hdl.handle.net/10993/44411
BioKC: a collaborative platform for systems biology model curation and annotation
English
Vega Moreno, Carlos Gonzalo mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Groues, Valentin mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Ostaszewski, Marek mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Schneider, Reinhard mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Satagopam, Venkata mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
2020
bioRxiv
Cold Spring Harbor Laboratory
No
[en] Systems Biology ; Knowledge Curation
[en] Curation of biomedical knowledge into standardised and inter-operable systems biology 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. Currently, these systems-level curation efforts concentrate around dedicated pathway databases, with a limited input from the research community. The demand for systems biology knowledge increases with new findings demonstrating elaborate relationships between multiple molecules, pathways and cells. This new challenge calls for novel collaborative tools and platforms allowing to improve the quality and the output of the curation process. In particular, in the current systems biology environment, curation tools lack reviewing features and are not well suited for an open, community-based curation workflows. An important concern is the complexity of the curation process and the limitations of the tools supporting it. Currently, systems-level curation combines model-building with diagram layout design. However, diagram editing tools offer limited annotation features. On the other hand, text-oriented tools have insufficient capabilities representing and annotating relationships between biological entities. Separating model curation and annotation from diagram editing enables iterative and distributed building of annotated models. Here, we present BioKC (Biological Knowledge Curation), a web-based collaborative platform for the curation and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML).Competing Interest StatementThe authors have declared no competing interest.
Fonds National de la Recherche - FnR
COVlit (14729738)
http://hdl.handle.net/10993/44411
10.1101/2020.10.01.322438
https://www.biorxiv.org/content/early/2020/10/03/2020.10.01.322438
The authors would like to thank the Luxembourg National Research Fund (FNR) for supporting this work through grant 14729738 for Covid19 Literature Biocuration, Text-mining And Semantic Web Technologies (COVlit) and the National Centre of Excellence in Research on Parkinson’s disease (NCER-PD [FNR/NCER13/BM/11264123])
FnR ; FNR11264123 > Rejko Krüger > NCER-PD > > 01/01/2015 > 30/11/2020 > 2013

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