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dc.contributor.authorLecca P
dc.contributor.authorNguyen T
dc.contributor.authorPriami C
dc.contributor.authorQuaglia P
dc.contributor.editorMayer B
dc.date.accessioned2020-06-25T08:37:59Z
dc.date.available2020-06-25T08:37:59Z
dc.date.issued2011
dc.identifier.isbn978-1-61779-026-3
dc.identifier.issn1064-3745
dc.identifier.urihttp://dx.doi.org/10.1007/978-1-61779-027-0_20
dc.identifier.urihttps://link.springer.com/protocol/10.1007/978-1-61779-027-0_20
dc.identifier.urihttps://bia.unibz.it/handle/10863/14413
dc.description.abstractWe provide a commented overview of the available databases for the systematic collection of pathway information and biological models essential for the interpretation of Omics data. Then, we present both the state of the art and the future challenges of network inference, a research area dealing with the deduction of reaction mechanisms from experimental Omics data. This approach represents one of the most challenging instances for making use of the huge amount of information gathered in the Omics era.en_US
dc.languageEnglish
dc.language.isoenen_US
dc.publisherHumana Pressen_US
dc.relation
dc.relation.ispartofseriesMethods in Molecular Biology;
dc.rights
dc.subjectSignalingen_US
dc.subjectPathway databaseen_US
dc.subjectBayesian inferenceen_US
dc.subjectNetwork inferenceen_US
dc.titleNetwork inference from time-dependent Omics dataen_US
dc.typeBook chapteren_US
dc.date.updated2020-06-25T08:03:57Z
dc.publication.titleBioinformatics for Omics Data: Methods and Protocols
dc.language.isiEN-GB
dc.description.fulltextnoneen_US


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