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Título:	ChainRank, a chain prioritisation method for contextualisation of biological networks
Autor/a:	Tényi, Ákos; Atauri Carulla, Ramón de; Gomez Cabrero, David; Cano Franco, Isaac; Clarke, Kim; Falciani, Francesco; Cascante i Serratosa, Marta; Roca, Josep; Maier, Dieter
Notas:	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).
Materia(s):	-Bioinformàtica -Biologia computacional -Proteïnes -Sistemes biològics -Bioinformatics -Computational biology -Proteins -Biological systems
Derechos:	cc-by (c) Tényi, Á. et al., 2016 http://creativecommons.org/licenses/by/3.0/es
Tipo de documento:	Artículo Artículo - Versión publicada
Editor:	BioMed Central
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