NDLI: A new preprocessing procedure for the haplotype inference problem

Content Provider	IEEE Xplore Digital Library
Author	Irurozki, E. Lozano, J.A.
Copyright Year	2009
Description	Author affiliation: Intelligent Systems Group, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Spain (Irurozki, E.; Lozano, J.A.)
Abstract	A haplotype is a DNA sequence that is inherited from one parent. They are especially important in the study of complex diseases since they contain more information than genotype data, so the next high priority phase in human genomics involves the development of a full Haplotype Map of human genome [1]. However, obtaining haplotype data is technically difficult and expensive. One of the computational methods for obtaining haplotype data from genotype data is the pure parsimony criterion, an approach known as Haplotype Inference by Pure Parsimony (HIPP). It has been proved to be an NP-hard problem. We present a new preprocessing method which drastically decreases the number of relevant haplotypes. Several algorithms need to preprocess data; for big problem instances this key procedure is even more important than the process. This preprocessing was eventually tested on real and simulated data applying a tabu search, and the performance of the resulting algorithm showed it to be competitive with the best actual solvers.
Starting Page	1320
Ending Page	1327
File Size	673744
Page Count	8
File Format	PDF
ISBN	9781424429585
DOI	10.1109/CEC.2009.4983097
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-18
Publisher Place	Norway
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Genomics Bioinformatics DNA Sequences Diseases NP-hard problem Inference algorithms Testing Discrete event simulation
Content Type	Text
Resource Type	Article

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