Haplotyping as perfect phylogeny: conceptual framework and efficient solutions
Proceedings of the sixth annual international conference on Computational biology
Model-based inference of haplotype block variation
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Perfect phylogeny and haplotype assignment
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Islands of Tractability for Parsimony Haplotyping
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Haplotyping with missing data via perfect path phylogenies
Discrete Applied Mathematics
Haplotyping Populations by Pure Parsimony: Complexity of Exact and Approximation Algorithms
INFORMS Journal on Computing
Haplotype inference by pure Parsimony
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
A hidden markov technique for haplotype reconstruction
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Algorithms for imperfect phylogeny haplotyping (IPPH) with a single homoplasy or recombination event
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
A polynomial case of the parsimony haplotyping problem
Operations Research Letters
Phylogeny - and parsimony-based haplotype inference with constraints
CPM'10 Proceedings of the 21st annual conference on Combinatorial pattern matching
Extended islands of tractability for parsimony haplotyping
CPM'10 Proceedings of the 21st annual conference on Combinatorial pattern matching
Phylogeny- and parsimony-based haplotype inference with constraints
Information and Computation
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The haplotype inference problem (HIP) asks to find a set of haplotypes which resolve a given set of genotypes. This problem is of enormous importance in many practical fields, such as the investigation of diseases, or other types of genetic mutations. In order to find the haplotypes that are as close as possible to the real set of haplotypes that comprise the genotypes, two models have been suggested which by now have become widely accepted: The perfect phylogeny model and the pure parsimony model. All known algorithms up till now for the above problem may find haplotypes that are not necessarily plausible, i.e. very rare haplotypes or haplotypes that were never observed in the population. In order to overcome this disadvantage we study in this paper, for the first time, a new constrained version of HIP under the above mentioned models. In this new version, a pool of plausible haplotypes $\widetilde{H}$ is given together with the set of genotypes G , and the goal is to find a subset $H \subseteq \widetilde{H}$ that resolves G . For the constrained perfect phylogeny haplotyping (CPPH) problem we provide initial insights and polynomial-time algorithms for some restricted cases that help understanding the complexity of that problem. We also prove that the constrained parsimony haplotyping (CPH) problem is fixed parameter tractable by providing a parameterized algorithm that applies an interesting dynamic programming technique for solving the problem.