Handbook of Computational Molecular Biology (Chapman & All/Crc Computer and Information Science Series)
Integer Programming Approaches to Haplotype Inference by Pure Parsimony
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Haplotyping Populations by Pure Parsimony: Complexity of Exact and Approximation Algorithms
INFORMS Journal on Computing
Efficient haplotype inference with boolean satisfiability
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Haplotype inference by pure Parsimony
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
SAT in bioinformatics: making the case with haplotype inference
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
HAPLO-ASP: Haplotype Inference Using Answer Set Programming
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Efficient haplotype inference with answer set programming
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Efficient haplotype inference with answer set programming
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
A new preprocessing procedure for the haplotype inference problem
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Efficient haplotype inference with combined CP and OR techniques
CPAIOR'08 Proceedings of the 5th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Combinatorial Optimization Solutions for the Maximum Quartet Consistency Problem
Fundamenta Informaticae - RCRA 2008 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Efficient and accurate haplotype inference by combining parsimony and pedigree information
ANB'10 Proceedings of the 4th international conference on Algebraic and Numeric Biology
| Hi-index | 0.00 |
Haplotype inference from genotype data is a key computational problem in bioinformatics, since retrieving directly haplotype information from DNA samples is not feasible using existing technology. One of the methods for solving this problem uses the pure parsimony criterion, an approach known as Haplotype Inference by Pure Parsimony (HIPP). Initial work in this area was based on a number of different Integer Linear Programming (ILP) models and branch and bound algorithms. Recent work has shown that the utilization of a Boolean Satisfiability (SAT) formulation and state of the art SAT solvers represents the most efficient approach for solving the HIPP problem. Motivated by the promising results obtained using SAT techniques, this paper investigates the utilization of modern Pseudo-Boolean Optimization (PBO) algorithms for solving the HIPP problem. The paper starts by applying PBO to existing ILP models. The results are promising, and motivate the development of a new PBO model (RPoly) for the HIPP problem, which has a compact representation and eliminates key symmetries. Experimental results indicate that RPoly outperforms the SAT-based approach on most problem instances, being, in general, significantly more efficient.