Biology – Quantitative Biology – Quantitative Methods
Scientific paper
2009-01-30
Biology
Quantitative Biology
Quantitative Methods
Scientific paper
A basic assumption of molecular biology is that proteins sharing close three-dimensional (3D) structures are likely to share a common function and in most cases derive from a same ancestor. Computing the similarity between two protein structures is therefore a crucial task and has been extensively investigated. Evaluating the similarity of two proteins can be done by finding an optimal one-to-one matching between their components, which is equivalent to identifying a maximum weighted clique in a specific "alignment graph". In this paper we present a new integer programming formulation for solving such clique problems. The model has been implemented using the ILOG CPLEX Callable Library. In addition, we designed a dedicated branch and bound algorithm for solving the maximum cardinality clique problem. Both approaches have been integrated in VAST (Vector Alignment Search Tool) - a software for aligning protein 3D structures largely used in NCBI (National Center for Biotechnology Information). The original VAST clique solver uses the well known Bron and Kerbosh algorithm (BK). Our computational results on real life protein alignment instances show that our branch and bound algorithm is up to 116 times faster than BK for the largest proteins.
Andonov Rumen
Malod-Dognin Noël
Yanev Nicola
No associations
LandOfFree
Solving Maximum Clique Problem for Protein Structure Similarity does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Solving Maximum Clique Problem for Protein Structure Similarity, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Solving Maximum Clique Problem for Protein Structure Similarity will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-424470