02093nas a2200253   4500008004100000022001400041245010500055210006900160260007300229300001400302490000700316520117300323653002601496653001901522653002001541653000901561653002801570100002401598700001801622700001901640700002601659700002601685856012801711       2007                        eng d  a0167-865500aUsing pseudo amino acid composition to predict protein subnuclear localization: approached with PSSM0 aUsing pseudo amino acid composition to predict protein subnuclea  aPO BOX 211, 1000 AE AMSTERDAM, NETHERLANDSbELSEVIER SCIENCE BVcOCT  a1610-16150 v283 a<p>Identification of Nuclear protein localization assumes significance as it can provide in depth insight for genome regulation and function annotation of novel proteins. A multiclass SVM classifier with various input features was employed for nuclear protein compartment identification. The input features include factor solution scores and evolutionary information (position specific scoring matrix (PSSM) score) apart from conventional dipeptide composition and pseudo amino acid composition. All the SVM classifiers with different sets of input features performed better than the previously available prediction classifiers. The jack-knife success rate thus obtained on the benchmark dataset constructed by Shen and Chou [Shen, H.B., Chou, K.C., 2005, Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition. Biochem. Biophys. Res. Commun. 337, 752-756] is 71.23%, indicating that the novel pseudo amino acid composition approach with PSSM and SVM classifier is very promising and may at least play a complimentary role to the existing methods. (c) 2007 Elsevier B.V. All rights reserved.</p>10afactor solution score10amulticlass SVM10anuclear protein10aPSSM10asubnuclear localization1 aMundra, Piyushkumar1 aKumar, Madhan1 aKumar, Krishna1 aJayaraman, Valadi, K.1 aKulkarni, Bhaskar, D.  uhttps://library.ncl.res.in/content/using-pseudo-amino-acid-composition-predict-protein-subnuclear-localization-approached-0