Reference : Closing the gap between formats for storing layout information in systems biology.
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/40903
Closing the gap between formats for storing layout information in systems biology.
English
Hoksza, David mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > > ; Charles University > Department of Software Engineering]
Gawron, Piotr mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Ostaszewski, Marek mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Hausenauer, Jan [Helmholtz Zentrum München > Institute of Computational Biology > > ; Technische Universität München - TUM > Department of Mathematics > > ; University of Bonn > Faculty of Mathematics and Natural Sciences]
Schneider, Reinhard mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
2019
Briefings in bioinformatics
Yes
International
1467-5463
1477-4054
England
[en] conversion ; data format ; molecular network ; network layout ; systems biology
[en] The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
http://hdl.handle.net/10993/40903
10.1093/bib/bbz067
https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbz067/5527141

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