Reverse engineering and analysis of large genome-scale gene networks

dc.contributor.author Aluru, Maneesha
dc.contributor.author Zola, Jaroslaw
dc.contributor.author Nettleton, Dan
dc.contributor.author Aluru, Srinivas
dc.contributor.author Nettleton, Dan
dc.contributor.department Statistics
dc.contributor.department Electrical and Computer Engineering
dc.contributor.department Genetics, Development and Cell Biology
dc.date 2019-08-22T08:00:30.000
dc.date.accessioned 2020-07-02T06:57:03Z
dc.date.available 2020-07-02T06:57:03Z
dc.date.copyright Sun Jan 01 00:00:00 UTC 2012
dc.date.issued 2013-01-01
dc.description.abstract <p>Reverse engineering the whole-genome networks of complex multicellular organisms continues to remain a challenge. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. To enable fast and accurate reconstruction of large networks, we developed Tool for Inferring Network of Genes (TINGe), a parallel mutual information (MI)-based program. The novel features of our approach include: (i) B-spline-based formulation for linear-time computation of MI, (ii) a novel algorithm for direct permutation testing and (iii) development of parallel algorithms to reduce run-time and facilitate construction of large networks. We assess the quality of our method by comparison with ARACNe (Algorithm for the Reconstruction of Accurate Cellular Networks) and GeneNet and demonstrate its unique capability by reverse engineering the whole-genome network of <em>Arabidopsis thaliana</em> from 3137 Affymetrix ATH1 GeneChips in just 9 min on a 1024-core cluster. We further report on the development of a new software Gene Network Analyzer (GeNA) for extracting context-specific subnetworks from a given set of seed genes. Using TINGe and GeNA, we performed analysis of 241 <em>Arabidopsis</em> AraCyc 8.0 pathways, and the results are made available through the web.</p>
dc.description.comments <p>This article is published as Aluru, Maneesha, Jaroslaw Zola, Dan Nettleton, and Srinivas Aluru. "Reverse engineering and analysis of large genome-scale gene networks." <em>Nucleic acids research</em> 41, no. 1 (2012): e24. doi: <a href="https://doi.org/10.1093/nar/gks904">10.1093/nar/gks904</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/188/
dc.identifier.articleid 1198
dc.identifier.contextkey 14824669
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/188
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90496
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/188/2013_Nettleton_ReverseEngineering.pdf|||Fri Jan 14 21:46:44 UTC 2022
dc.source.uri 10.1093/nar/gks904
dc.subject.disciplines Bioinformatics
dc.subject.disciplines Biomedical
dc.subject.disciplines Computational Biology
dc.subject.disciplines Genetics and Genomics
dc.title Reverse engineering and analysis of large genome-scale gene networks
dc.type article
dc.type.genre article
dspace.entity.type Publication
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