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Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí y học Molecular Biology cung cấp cho các bạn kiến thức về ngành sinh học đề tài: Protein sequence and structure alignments within one framework. | Algorithms for Molecular Biology BioMed Central Research Protein sequence and structure alignments within one framework Gundolf Schenk Thomas Margraf and Andrew E Torda Address Centre for Bioinformatics University of Hamburg Bundesstr. 43 D-20146 Hamburg Germany Email Gundolf Schenk - schenk@zbh.uni-hamburg.de Thomas Margraf- margraf@zbh.uni-hamburg.de Andrew E Torda - torda@zbh.uni-hamburg.de Corresponding author Open Access Published I April 2008 Received 29 January 2008 Algorithms for Molecular Biology 2008 3 4 doi 10.1186 1748-7188-3-4 Accepted 1 April 2008 This article is available from http www.almob.Org content 3 1 4 2008 Schenk et al licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons.org licenses by 2.0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background Protein structure alignments are usually based on very different techniques to sequence alignments. We propose a method which treats sequence structure and even combined sequence structure in a single framework. Using a probabilistic approach we calculate a similarity measure which can be applied to fragments containing only protein sequence structure or both simultaneously. Results Proof-of-concept results are given for the different problems. For sequence alignments the methodology is no better than conventional methods. For structure alignments the techniques are very fast reliable and tolerant of a range of alignment parameters. Combined sequence and structure alignments may provide a more reliable alignment for pairs of proteins where pure structural alignments can be misled by repetitive elements or apparent symmetries. Conclusion The probabilistic framework has an elegance in principle merging sequence and structure descriptors .
