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.
Computational challenges in structural and functional genomics
IBM Systems Journal - Deep computing for the life sciences
Opportunities for Combinatorial Optimization in Computational Biology
INFORMS Journal on Computing
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
Lagrangian approaches for a class of matching problems in computational biology
Computers & Mathematics with Applications
Optimal protein threading by cost-splitting
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
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FROST (Fold Recognition-Oriented Search Tool) is a software whose purpose is to assign a 3D structure to a protein sequence. It is based on a series of filters and uses a database of about 1200 known 3D structures, each one associated with empirically determined score distributions. FROST uses these distributions to normalize the score obtained when a protein sequence is aligned with a particular 3D structure. Computing these distributions is extremely time consuming; it requires solving about 1,200,000 hard combinatorial optimization problems and takes about 40 days on a 2.4 GHz computer. This paper describes how FROST has been successfully redesigned and structured in modules and independent tasks. The new package organization allows these tasks to be distributed and executed in parallel using a centralized dynamic load balancing strategy. On a cluster of 12 PCs, computing the score distributions takes now about 3 days which represents a parallelization efficiency of about 1.