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Dimensionality reduction in computational demarcation of protein tertiary structures

DSpace at IIT Bombay

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Title Dimensionality reduction in computational demarcation of protein tertiary structures
 
Creator JOSHI, RR
PANIGRAHI, PR
PATIL, RN
 
Subject Logistic regression
Principal component analysis
Protein structural classes
Quantitative features of tertiary folds
SCOP database
SECONDARY STRUCTURE-CONTENT
STRUCTURE PREDICTION
DISTANCE MATRICES
CLASSIFICATION
NETWORK
PROPAINOR
ALIGNMENT
 
Description Predictive classification of major structural families and fold types of proteins is investigated deploying logistic regression. Only five to seven dimensional quantitative feature vector representations of tertiary structures are found adequate. Results for benchmark sample of non-homologous proteins from SCOP database are presented. Importance of this work as compared to homology modeling and best-known quantitative approaches is highlighted.
 
Publisher SPRINGER
 
Date 2014-10-16T12:22:35Z
2014-10-16T12:22:35Z
2012
 
Type Article
 
Identifier JOURNAL OF MOLECULAR MODELING, 18(6)2741-2754
http://dx.doi.org/10.1007/s00894-011-1223-0
http://dspace.library.iitb.ac.in/jspui/handle/100/15535
 
Language en