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DISCO: A New Algorithm for Detecting 3D Protein Structure Similarity

Abstract : Protein structure similarity is one of the most important aims pursued by bioinformatics and structural biology, nowadays. Although quite a few similarity methods have been proposed lately, yet fresh algorithms that fulfill new preconditions are needed to serve this purpose. In this paper, we provide a new similarity measure for 3D protein structures that detects not only similar structures but also similar substructures to a query protein, supporting both multiple and pairwise comparison procedures and combining many comparison characteristics. In order to handle similarity queries we utilize efficient and effective indexing techniques such as M-trees and we provide interesting results using real, previously tested protein data sets.
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Nantia Iakovidou, Eleftherios Tiakas, Konstantinos Tsichlas. DISCO: A New Algorithm for Detecting 3D Protein Structure Similarity. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. pp.622-631, ⟨10.1007/978-3-642-33412-2_64⟩. ⟨hal-01523057⟩

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