01325nas a2200229   4500008004100000022001400041245008900055210006900144260005700213300001400270490000700284520046000291653002400751653003300775653003100808653004400839653001800883100002200901700003000923700002200953856012000975       2012                        eng d  a1610-294000aDimensionality reduction in computational demarcation of protein tertiary structures0 aDimensionality reduction in computational demarcation of protein  a233 SPRING ST, NEW YORK, NY 10013 USAbSPRINGERcJUN  a2741-27540 v183 a<p>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.</p>10aLogistic regression10aPrincipal component analysis10aProtein structural classes10aQuantitative features of tertiary folds10aSCOP database1 aJoshi, Rajani, R.1 aPanigrahi, Priyabrata, R.1 aPatil, Reshma, N.  uhttps://library.ncl.res.in/content/dimensionality-reduction-computational-demarcation-protein-tertiary-structures-0