Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/68878
Title: ChainRank, a chain prioritisation method for contextualisation of biological networks
Author: Tényi, Á.
Atauri Carulla, Ramón de
Gomez-Cabrero, David
Cano, Isaac
Clarke, Kim
Falciani, Francesco
Cascante i Serratosa, Marta
Roca, Josep
Maier, Dieter
Keywords: Bioinformàtica
Biologia computacional
Proteïnes
Sistemes biològics
Bioinformatics
Computational biology
Proteins
Biological systems
Issue Date: 5-Jan-2016
Publisher: BioMed Central
Abstract: Advances in high throughput technologies and growth of biomedical knowledge have contributed to an exponential increase in associative data. These data can be represented in the form of complex networks of biological associations, which are suitable for systems analyses. However, these networks usually lack both, context specificity in time and space as well as the distinctive borders, which are usually assigned in the classical pathway view of molecular events (e.g. signal transduction). This complexity and high interconnectedness call for automated techniques that can identify smaller targeted subnetworks specific to a given research context (e.g. a disease scenario).
Note: Reproducció del document publicat a: http://dx.doi.org/10.1186/s12859-015-0864-x
It is part of: Bmc Bioinformatics, 2016, vol. 17, num. 1, p. 1-17
Related resource: http://dx.doi.org/10.1186/s12859-015-0864-x
URI: http://hdl.handle.net/2445/68878
ISSN: 1471-2105
Appears in Collections:Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer)
Articles publicats en revistes (Bioquímica i Biomedicina Molecular)

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