Reference : BioKC: a platform for quality controlled curation and annotation of systems biology models

	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Life sciences : Biochemistry, biophysics & molecular biology
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/44474

Title :	BioKC: a platform for quality controlled curation and annotation of systems biology models
Language :	English
Author, co-author :	Vega Moreno, Carlos Gonzalo [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Groues, Valentin [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Ostaszewski, Marek [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Satagopam, Venkata [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Schneider, Reinhard [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Publication date :	4-Sep-2020
Peer reviewed :	No
Audience :	International
Event name :	European Conference on Computational Biology
Event date :	from 31-8-2020 to 8-9-2020
Event place (city) :	Virtual
Keywords :	[en] Systems Biology ; Knowledge Curation
Abstract :	[en] Standardisation of biomedical knowledge into systems biology models is essential for the study of the biological function. However, biomedical knowledge curation is a laborious manual process aggravated by the ever increasing growth of biomedical literature. High quality curation currently relies on pathway databases where outsider participation is minimal. The increasing demand of systems biology knowledge presents new challenges regarding curation, calling for new collaborative functionalities to improve quality control of the review process. These features are missing in the current systems biology environment, whose tools are not well suited for an open community-based model curation workflow. On one hand, diagram editors such as CellDesigner or Newt provide limited annotation features. On the other hand, most popular text annotations tools are not aimed for biomedical text annotation or model curation. Detaching the model curation and annotation tasks from diagram editing improves model iteration and centralizes the annotation of such models with supporting evidence. In this vain, we present BioKC, a web-based platform for systematic quality-controlled collaborative curation and annotation of biomedical knowledge following the standard data model from Systems Biology Markup Language (SBML).
Funders :	Fonds National de la Recherche - FnR
Permalink :	http://hdl.handle.net/10993/44474
DOI :	10.5281/zenodo.4033071
Other URL :	https://doi.org/10.5281/zenodo.4033071
Commentary :	The authors would like to thank the Luxembourg National Research Fund (FNR) for supporting this work through grant: 14729738 (COVlit).

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access BioKC Poster BioNetVisA 2020.pdf Author postprint 2.58 MB View/Open Additional material(s): File Commentary Size Access Open access BioKC Slides BioNetVisA 2020.pptx Presentation Slides 21.63 MB View/Open

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