DocumentCode :
419342
Title :
Inferring genetic networks from microarray data
Author :
Martin, Shawn ; Davidson, George ; May, Elebeoba ; Faulon, Jean-Loup ; Werner-Washburne, Margaret
Author_Institution :
Comput. Biol., Sandia Nat. Labs., Albuquerque, NM, USA
fYear :
2004
fDate :
16-19 Aug. 2004
Firstpage :
566
Lastpage :
569
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.
Keywords :
biology computing; genetics; inference mechanisms; time series; genetic networks; inference; network discovery; time series microarray data; Bioinformatics; Clustering algorithms; Computational biology; Genetics; Inference algorithms; Laboratories; Logic; Partitioning algorithms; Stability; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
Print_ISBN :
0-7695-2194-0
Type :
conf
DOI :
10.1109/CSB.2004.1332498
Filename :
1332498
Link To Document :
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