Integer and combinatorial optimization
Integer and combinatorial optimization
On the approximation of protein threading
Theoretical Computer Science - Special issue: Genome informatics
Computational Biology at the Beginning of the Post-genomic Era
Informatics - 10 Years Back. 10 Years Ahead.
Solving the Protein Threading Problem in Parallel
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Integer programming models for computational biology problems
Journal of Computer Science and Technology - Special issue on bioinformatics
Opportunities for Combinatorial Optimization in Computational Biology
INFORMS Journal on Computing
FROST: Revisited and Distributed
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 7 - Volume 08
Parallel divide and conquer approach for the protein threading problem: Research Articles
Concurrency and Computation: Practice & Experience - High Performance Computational Biology
Protein Threading: From Mathematical Models to Parallel Implementations
INFORMS Journal on Computing
An Efficient Lagrangian Relaxation for the Contact Map Overlap Problem
WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
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In this paper, we use integer programming approach for solving a hard combinatorial optimization problem, namely protein threading. For this sequence-to-structure alignment problem we apply cost-splitting technique to derive a new Lagrangian dual formulation. The optimal solution of the dual is sought by an algorithm of polynomial complexity. For most of the instances the dual solution provides an optimal or near-optimal (with negligible duality gap) alignment. The speed-up with respect to the widely promoted approach for solving the same problem in [17] is from 100 to 250 on computationally interesting instances. Such a performance turns computing score distributions, the heaviest task when solving PTP, into a routine operation.