Literature DB >> 20134430

Expander: from expression microarrays to networks and functions.

Igor Ulitsky1, Adi Maron-Katz, Seagull Shavit, Dorit Sagir, Chaim Linhart, Ran Elkon, Amos Tanay, Roded Sharan, Yosef Shiloh, Ron Shamir.   

Abstract

A major challenge in the analysis of gene expression microarray data is to extract meaningful biological knowledge out of the huge volume of raw data. Expander (EXPression ANalyzer and DisplayER) is an integrated software platform for the analysis of gene expression data, which is freely available for academic use. It is designed to support all the stages of microarray data analysis, from raw data normalization to inference of transcriptional regulatory networks. The microarray analysis described in this protocol starts with importing the data into Expander 5.0 and is followed by normalization and filtering. Then, clustering and network-based analyses are performed. The gene groups identified are tested for enrichment in function (based on Gene Ontology), co-regulation (using transcription factor and microRNA target predictions) or co-location. The results of each analysis step can be visualized in a number of ways. The complete protocol can be executed in approximately 1 h.

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Year:  2010        PMID: 20134430     DOI: 10.1038/nprot.2009.230

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  62 in total

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Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

8.  Cluster analysis and display of genome-wide expression patterns.

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  108 in total

1.  Molecular profiling of cytomegalovirus-induced human CD8+ T cell differentiation.

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Review 7.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

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9.  Differential co-expression framework to quantify goodness of biclusters and compare biclustering algorithms.

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Journal:  Algorithms Mol Biol       Date:  2010-05-28       Impact factor: 1.405

10.  Towards computational prediction of microRNA function and activity.

Authors:  Igor Ulitsky; Louise C Laurent; Ron Shamir
Journal:  Nucleic Acids Res       Date:  2010-06-24       Impact factor: 16.971

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