Inferring genetic networks from microarray data

Shawn Martin, George Davidson, Elebeoba May, Jean Loup Faulon, Margaret Werner-Washburne

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

1 Scopus citations

Abstract

In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three major challenges are 1) inferring the network; 2) estimating the stability of the inferred network; and 3) making the network visually accessible to the user. Here we describe a method, tested on publicly available time series microarray data, which addresses these concerns.

Original languageEnglish (US)
Title of host publicationProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
Pages566-569
Number of pages4
StatePublished - 2004
EventProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA, United States
Duration: Aug 16 2004Aug 19 2004

Publication series

NameProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

Other

OtherProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
CountryUnited States
CityStanford, CA
Period8/16/048/19/04

ASJC Scopus subject areas

  • Engineering(all)

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