Literature DB >> 17164284

Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data.

Gilad Lerman1, Joseph McQuown, Alexandre Blais, Brian D Dynlacht, Guangliang Chen, Bud Mishra.   

Abstract

UNLABELLED: We present a fast, versatile and adaptive-multiscale algorithm for analyzing a wide-variety of DNA microarray data. Its primary application is in normalization of array data as well as subsequent identification of 'enriched targets', e.g. differentially expressed genes in expression profiling arrays and enriched sites in ChIP-on-chip experimental data. We show how to accommodate the unique characteristics of ChIP-on-chip data, where the set of 'enriched targets' is large, asymmetric and whose proportion to the whole data varies locally. SUPPLEMENTARY INFORMATION: Supplementary figures, related preprint, free software as well as our raw DNA microarray data with PCR validations are available at http://www.math.umn.edu/~lerman/supp/bioinfo06 as well as Bioinformatics online.

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Year:  2006        PMID: 17164284     DOI: 10.1093/bioinformatics/btl606

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

1.  Protein complex, gene, and regulatory modules in cancer heterogeneity.

Authors:  Nikolaos A Papanikolaou; Athanasios G Papavassiliou
Journal:  Mol Med       Date:  2008 Sep-Oct       Impact factor: 6.354

2.  Detailing regulatory networks through large scale data integration.

Authors:  Curtis Huttenhower; K Tsheko Mutungu; Natasha Indik; Woongcheol Yang; Mark Schroeder; Joshua J Forman; Olga G Troyanskaya; Hilary A Coller
Journal:  Bioinformatics       Date:  2009-10-13       Impact factor: 6.937

  2 in total

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