Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Hardness of Approximating Problems on Cubic Graphs
CIAC '97 Proceedings of the Third Italian Conference on Algorithms and Complexity
Journal of Functional Programming
The Haplotyping problem: an overview of computational models and solutions
Journal of Computer Science and Technology
Integer Programming Approaches to Haplotype Inference by Pure Parsimony
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Islands of Tractability for Parsimony Haplotyping
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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
On the complexity of several haplotyping problems
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
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Haplotype Inference Constrained by Plausible Haplotype Data
CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
Haplotype Inference Constrained by Plausible Haplotype Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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The problem Parsimony Haplotyping (PH) asks for the smallest set of haplotypes which can explain a given set of genotypes, and the problem Minimum Perfect Phylogeny Haplotyping (MPPH) asks for the smallest such set which also allows the haplotypes to be embedded in a perfect phylogeny evolutionary tree, a well-known biologically-motivated data structure. For PH we extend recent work of [17] by further mapping the interface between “easy” and “hard” instances, within the framework of (k,l)-bounded instances. By exploring, in the same way, the tractability frontier of MPPH we provide the first concrete, positive results for this problem, and the algorithms underpinning these results offer new insights about how MPPH might be further tackled in the future. In both PH and MPPH intriguing open problems remain.