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
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Creator |
JOSHI, RR
PANIGRAHI, PR PATIL, RN |
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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 |
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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.
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Publisher |
SPRINGER
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Date |
2014-10-16T12:22:35Z
2014-10-16T12:22:35Z 2012 |
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Type |
Article
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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 |
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Language |
en
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