DocumentCode :
504456
Title :
Fitness function for evolutionary system to predict unknown gene regulatory networks
Author :
Maeshiro, Tetsuya ; Shimohara, Katsunori ; Nakayama, Shin-Ichi
Author_Institution :
Sch. of Libr. & Inf. Sci., Univ. of Tsukuba, Ibaraki, Japan
fYear :
2009
fDate :
18-21 Aug. 2009
Firstpage :
2722
Lastpage :
2727
Abstract :
This paper proposes a method, denoted pulse flux analysis, to evaluate computationally generated gene regulatory networks, without using biological knowledge related to the target gene regulatory network. Furthermore, the quantification of networks enables the ranking of predicted gene regulatory networks, and prioritization of network candidates to examine by biological experiments is also possible. A short pulse is injected to input nodes of the target network, and the response behavior is analyzed. The method also detects logical ambiguities that cannot be revealed by methods that analyze the static structure of networks. The presented method is incorporated into our system to predict gene regulatory networks, which relies on evolutionary mechanism and high simulation speed.
Keywords :
genetic algorithms; denoted pulse flux analysis; evolutionary system; fitness function; gene regulatory network prediction; Biochemistry; Bioinformatics; Biological system modeling; Biology computing; Computational modeling; Computer networks; Electronic mail; Genomics; Organisms; Proteins; Gene regulatory network; evolutionary system; fitness; simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
ICCAS-SICE, 2009
Conference_Location :
Fukuoka
Print_ISBN :
978-4-907764-34-0
Electronic_ISBN :
978-4-907764-33-3
Type :
conf
Filename :
5333375
Link To Document :
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