Maximum likelihood model based on minor allele frequencies and weighted Max-SAT formulation for haplotype assembly.

Human haplotypes include essential information about SNPs, which in turn provide valuable information for such studies as finding relationships between some diseases and their potential genetic causes, e.g., for Genome Wide Association Studies.

An improved heuristic for haplotype inference.

Haplotypes include essential SNP information used for a variety of purposes such as investigating potential links between certain diseases and genetic variations. Given a set of genotypes, the haplotype inference problem based on pure parsimony is the problem of finding a minimum set of haplotypes that explains all the given genotypes. The problem is especially important because, while it is fairly inexpensive to obtain genotypes, other approaches to obtaining haplotypes are significantly expensive.

An enhanced beam search algorithm for the Shortest Common Supersequence Problem.

The Shortest Common Supersequence Problem asks to obtain a shortest string that is a supersequence of every member of a given set of strings. It has applications, among others, in data compression and oligonucleotide microarray production. The problem is NP-hard, and the existing exact solutions are impractical for large instances.

RETRACTED: Corrigendum to "Improved haplotype assembly using Xor genotypes" [J. Theor. Biol. 298 (2012) 122-130].

This Corrigendum has been withdrawn at the request of the authors. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.

A hyper-heuristic for the Longest Common Subsequence problem.

The Longest Common Subsequence Problem is the problem of finding a longest string that is a subsequence of every member of a given set of strings. It has applications in FPGA circuit minimization, data compression, and bioinformatics, among others. The problem is NP-hard in its general form, which implies that no exact polynomial-time algorithm currently exists for the problem.

Improved haplotype assembly using Xor genotypes.

Given a set of aligned fragments, haplotype assembly is the problem of finding the haplotypes from which the fragments have been read. The problem is important because haplotypes contain SNP information, which is essential to many genomic analyses such as the analysis of potential association between certain diseases and genetic variations. The current state-of-the-art haplotype assembly algorithm, HapSAT, does not exploit genotype information and only receives a read matrix as input.

A hybrid metaheuristic for closest string problem.

The Closest String Problem (CSP) is an optimisation problem, which is to obtain a string with the minimum distance from a number of given strings. In this paper, a new metaheuristic algorithm is investigated for the problem, whose main feature is relatively high speed in obtaining good solutions, which is essential when the input size is large. The proposed algorithm is compared with four recent algorithms suggested for the problem, outperforming them in more than 98% of the cases.

Effective haplotype assembly via maximum Boolean satisfiability.

The haplotype assembly problem seeks the haplotypes of an individual from which a set of aligned SNP fragments are available. The problem is important as the haplotypes contain all the SNP information, which is essential to such studies as the analysis of the association between specific diseases and their potential genetic causes. Using Minimum Error Correction as the objective function, the problem is NP-hard, which raises the demand for effective yet affordable solutions.