DocumentCode
3561876
Title
Training finite state machines to improve PCR primer design
Author
Ashlock, Dan ; Wittrock, Andrew ; Wen, Tsui-Jung
Author_Institution
Dept. of Math., Iowa State Univ., Ames, IA, USA
Volume
1
fYear
2002
Firstpage
13
Lastpage
18
Abstract
We present preliminary results on training finite state machines (FSMs) as good/bad classifiers for polymerase chain reaction (PCR) primers. Novel features of the work presented include hybridization of multiple populations of FSMs and an incremental fitness function. The system presented here is a post-production add-on to a standard primer picking program intended to compensate for organism and lab specific factors
Keywords
DNA; biology computing; finite state machines; learning (artificial intelligence); pattern classification; DNA; PCR primers; finite state machines; genetic mapping; hybridization; pattern classification; polymerase chain reaction; training data; Annealing; Automata; Bioinformatics; Computer science; DNA; Genetics; Mathematics; Organisms; Polymers; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Print_ISBN
0-7803-7282-4
Type
conf
DOI
10.1109/CEC.2002.1006202
Filename
1006202
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