Stochastic local search for large-scale instances of the haplotype inference problem by pure parsimony

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Stochastic local search for large-scale instances of the haplotype inference problem by pure parsimony

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable approach to the problem is to encode it as a com...

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Stochastic local search for large-scale instances of the Haplotype Inference Problem by Parsimony

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable approach to the problem is to encode it as a com...

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Flexible Stochastic Local Search for Haplotype Inference

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable approach to the problem is to encode it as a com...

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Toward an algebraic understanding of haplotype inference by pure parsimony.

Haplotype inference by pure parsimony (HIPP) is known to be NP-Hard. Despite this, many algorithms successfully solve HIPP instances on simulated and real data. In this paper, we explore the connection between algebraic rank and the HIPP problem, to help identify easy and hard instances of the problem. The rank of the input matrix is known to be a lower bound on the size an optimal HIPP solutio...

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Haplotype Inference by Pure Parsimony via Genetic Algorithm

Haplotypes are specially important in the study of complex diseases since they contain more information about gene alleles than genotype data. However, getting haplotype data via experiments methods is techniquely difficult and expensive. Thus, haplotype inference through computational methods is practical and attractive. There are several models for inferrings haplotype from population genotyp...

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ژورنال

عنوان ژورنال: Journal of Algorithms

سال: 2008

ISSN: 0196-6774

DOI: 10.1016/j.jalgor.2008.02.004