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Domain position prediction based on sequence information by using fuzzy mean operator
Author(s) -
Jing Runyu,
Sun Jing,
Wang Yuelong,
Li Menglong
Publication year - 2015
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.24833
Subject(s) - sequence (biology) , position (finance) , domain (mathematical analysis) , operator (biology) , computer science , fuzzy logic , artificial intelligence , data mining , mathematics , algorithm , chemistry , mathematical analysis , business , biochemistry , finance , repressor , transcription factor , gene
ABSTRACT The prediction of protein domain region is an advantageous process on the study of protein structure and function. In this study, we proposed a new method, which is composed of fuzzy mean operator and region division, to predict the particular positions of domains in a target protein based on its sequence. The whole sequence is aligned and scored by using fuzzy mean operator, and the final determination of domain region position is realized by region division. A published benchmark is used for the comparison with previous researches. In addition, we generate two extra datasets to examine the stability of this method. Finally, the prediction accuracy of independent test dataset achieved by our method was up to 84.13%. We wish that this method could be useful for related researches. Proteins 2015; 83:1462–1469. © 2015 Wiley Periodicals, Inc.