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Meta-analysis of Protein Structural Alignment
Conference proceeding

Meta-analysis of Protein Structural Alignment

Jim Havrilla and Ahmet Sacan
2012 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS (BIBMW), pp 72-76
01 Jan 2012

Abstract

Computer Science, Interdisciplinary Applications Life Sciences & Biomedicine Mathematical & Computational Biology Science & Technology Computer Science Medical Informatics Technology
The three-dimensional structure of a protein molecule provides significant insight into its biological function. Structural alignment of proteins is an important and widely performed task in the analysis of protein structures, whereby functionally and evolutionarily important segments are identified. However, structural alignment is a computationally difficult problem and a large number of heuristics introduced to solve it do not agree on their results. Consequently, there is no widely accepted solution to the structure alignment problem. In this study, we present a meta-analysis approach to generate a reoptimized, best-of-all result using the alignments generated from several popular methods. Evaluations of the methods on a large set of benchmark pairwise alignments indicate that TM-align provides superior alignments (except for RMSD), compared to other methods we have surveyed. Smolign provides smaller cores than other methods with best RMSD values. The re-optimization of the alignments using TM-align's optimization method does not alter the relative performance of the methods. Additionally, visualization approaches to delineate the relationships of the alignment methods have been performed and their results provided.

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Web of Science research areas
Computer Science, Interdisciplinary Applications
Mathematical & Computational Biology
Medical Informatics
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