Identifying submodules of cellular regulatory networks

Guido Sanguinetti, Magnus Rattray, Neil D. Lawrence

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    Recent high throughput techniques in molecular biology have brought about the possibility of directly identifying the architecture of regulatory networks on a genome-wide scale. However, the computational task of estimating fine-grained models on a genome-wide scale is daunting. Therefore, it is of great importance to be able to reliably identify submodules of the network that can be effectively modelled as independent subunits. In this paper we present a procedure to obtain submodules of a cellular network by using information from gene-expression measurements. We integrate network architecture data with genome-wide gene expression measurements in order to determine which regulatory relations are actually confirmed by the expression data. We then use this information to obtain non-trivial submodules of the regulatory network using two distinct algorithms, a naive exhaustive algorithm and a spectral algorithm based on the eigendecomposition of an affinity matrix. We test our method on two yeast biological data sets, using regulatory information obtained from chromatin immunoprecipitation. © Springer-Verlag Berlin Heidelberg 2006.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.
    PublisherSpringer Nature
    Number of pages13
    ISBN (Print)3540461663, 9783540461661
    Publication statusPublished - 2006
    EventInternational Conference on Computational Methods in Systems Biology, CMSB 2006 - Trento
    Duration: 1 Jul 2006 → …

    Publication series

    NameLecture Notes in Computer Science


    ConferenceInternational Conference on Computational Methods in Systems Biology, CMSB 2006
    Period1/07/06 → …


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