Book ChapterDOI
Identifying submodules of cellular regulatory networks
Guido Sanguinetti,Magnus Rattray,Neil D. Lawrence +2 more
- pp 155-168
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TLDR
This paper integrates network architecture data with genome-wide gene expression measurements in order to determine which regulatory relations are actually confirmed by the expression data, and obtains 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.Abstract:
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.read more
Citations
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Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling
TL;DR: Using singular value decomposition in transforming genome-wide expression data from genes x arrays space to reduced diagonalized "eigengenes" x "eigenarrays" space gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype.
Journal ArticleDOI
MMG: a probabilistic tool to identify submodules of metabolic pathways.
TL;DR: Mixture Model on Graphs (MMG), a novel probabilistic model to identify differentially expressed submodules of biological networks and pathways is introduced, which can easily incorporate information about weights in the network, is robust against missing data and can be easily generalized to directed networks.
References
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Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization
Paul T. Spellman,Gavin Sherlock,Gavin Sherlock,Michael Q. Zhang,Vishwanath R. Iyer,Kirk R. Anders,Michael B. Eisen,Patrick O. Brown,Patrick O. Brown,David Botstein,Bruce Futcher +10 more
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An efficient algorithm for large-scale detection of protein families
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Journal ArticleDOI
Transcriptional Regulatory Networks in Saccharomyces cerevisiae
Tong Ihn Lee,Nicola J. Rinaldi,François Robert,Duncan T. Odom,Ziv Bar-Joseph,Georg K. Gerber,Nancy M. Hannett,Christopher T. Harbison,Craig M. Thompson,Itamar Simon,Julia Zeitlinger,Ezra G. Jennings,Heather L. Murray,D. Benjamin Gordon,Bing Ren,John J. Wyrick,Jean-Bosco Tagne,Thomas L. Volkert,Ernest Fraenkel,David K. Gifford,Richard A. Young +20 more
TL;DR: This work determines how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells, and identifies network motifs, the simplest units of network architecture, and demonstrates that an automated process can use motifs to assemble a transcriptional regulatory network structure.
Journal ArticleDOI
Transcriptional regulatory code of a eukaryotic genome
Christopher T. Harbison,D. Benjamin Gordon,Tong Ihn Lee,Nicola J. Rinaldi,Kenzie D MacIsaac,Timothy Danford,Nancy M. Hannett,Jean-Bosco Tagne,David B. Reynolds,Jane Yoo,Ezra G. Jennings,Julia Zeitlinger,Dmitry K. Pokholok,Manolis Kellis,Manolis Kellis,P. Alex Rolfe,Ken T. Takusagawa,Eric S. Lander,Eric S. Lander,David K. Gifford,David K. Gifford,Ernest Fraenkel,Richard A. Young,Richard A. Young +23 more
TL;DR: An initial map of yeast's transcriptional regulatory code is constructed by identifying the sequence elements that are bound by regulators under various conditions and that are conserved among Saccharomyces species.
Journal ArticleDOI
Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals
Xiaohui Xie,Jun Lu,Edward J. Kulbokas,Todd R. Golub,Vamsi K. Mootha,Kerstin Lindblad-Toh,Eric S. Lander,Eric S. Lander,Manolis Kellis,Manolis Kellis +9 more
TL;DR: In this article, a comparative analysis of the human, mouse, rat and dog genomes is presented to create a systematic catalogue of common regulatory motifs in promoters and 3' untranslated regions (3' UTRs).
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