DocumentCode
2688357
Title
Efficient assembling of genome fragments using genetic algorithm enhanced by heuristic search
Author
Kikuchi, Satoko ; Chakraborty, Goutam
Author_Institution
Iwate Prefectural Univ., Iwate
fYear
2007
fDate
25-28 Sept. 2007
Firstpage
305
Lastpage
312
Abstract
Shotgun sequencing is the state-of-the-art to decode genome sequence. However this technique needs a lot of fragments. Combining those fragments correctly requires enormous computational cost. In our previous work we have shown how genetic algorithm (GA) could solve this problem efficiently. In this work, we added two heuristic ideas with GA to make it more efficient. One is chromosome reduction (CRed) step which shorten the length of the chromosomes, participating in genetic search, to improve the efficiency. The other is chromosome refinement (CRef) step which is a greedy heuristics, rearranging the bits using domain knowledge, to locally improve the fitness of chromosomes. With this hybridization and simple scaffold list, we could obtain longer contigs and scaffolds using GA. We experimented using three actual genome data to test our algorithm. We succeed in restructuring contigs covering about 90% of target genome sequences, and assembling about 500~1,000 fragments into 3 ~ 11 scaffolds. All the experiments were done using common desktop machines.
Keywords
biology computing; data analysis; genetic algorithms; genetics; search problems; chromosome length shortening; chromosome reduction; chromosome refinement; contig restructuring; domain knowledge; genetic algorithm; genetic search; genome fragment assembling; genome sequence decoding; greedy heuristics; heuristic search; hybridization; scaffolds; shotgun sequencing; Assembly systems; Bioinformatics; Biological cells; Computational efficiency; Decoding; Genetic algorithms; Genomics; Humans; Information science; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location
Singapore
Print_ISBN
978-1-4244-1339-3
Electronic_ISBN
978-1-4244-1340-9
Type
conf
DOI
10.1109/CEC.2007.4424486
Filename
4424486
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