Using Bregmann Divergence Regularized Machine for Comparison of Molecular Local Structures

Raissa RELATOR  Nozomi NAGANO  Tsuyoshi KATO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E99-D   No.1   pp.275-278
Publication Date: 2016/01/01
Publicized: 2015/10/06
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2015EDL8104
Type of Manuscript: LETTER
Category: Artificial Intelligence, Data Mining
Keyword: 
machine learning,  Bregmann divergence,  molecular structures,  local structure comparison,  

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Summary: 
Although many 3D structures have been solved for proteins to date, functions of some proteins remain unknown. To predict protein functions, comparison of local structures of proteins with pre-defined model structures, whose functions have been elucidated, is widely performed. For the comparison, the root mean square deviation (RMSD) has been used as a conventional index. In this work, adaptive deviation was incorporated, along with Bregmann Divergence Regularized Machine, in order to detect analogous local structures with such model structures more effectively than the conventional index.