Shi, J.Y., Zhang, S.W., Pan, Q., Cheng, Y.-M., Xie, J. (2007) Prediction of protein subcellular localization by support vector machines using multi-scale energy and pseudo mino acid composition. Amino Acids, 33, 69-74.

has been cited by the following article:

• TITLE: Cell-PLoc 2.0: an improved package of web-servers for predicting subcellular localization of proteins in various organisms

  AUTHORS: Kuo-Chen Chou, Hong-Bin Shen

  KEYWORDS: Euk-mPLoc 2.0; Hum-mPLoc 2.0;Plant-mPLoc; Gpos-mPLoc; Gneg-mPLoc;Virus-mPLoc; Higher-level GO approach; Ab-initio approach; Functional domain; Sequential evolution;

  JOURNAL NAME: Natural Science, Vol.2 No.10, October 29, 2010

  ABSTRACT: Cell-PLoc 2.0 is a package of web-servers evolved from Cell-PLoc (Chou, K.C. & Shen, H.B., Nature Protocols, 2008, 2:153-162) by a top-down approach to improve the power for predicting subcellular localization of proteins in various organisms. It contains six predictors: Euk-mPLoc 2.0, Hum-mPLoc 2.0, Plant-mPLoc, Gpos-mPLoc, Gneg-mPLoc, and Virus-mPLoc, specialized for eukaryotic, human, plant, Gram- positive bacterial, Gram-negative bacterial, and virus proteins, respectively. Compared with Cell-PLoc, the predictors in the Cell-PLoc 2.0 have the following advantageous features: (1) they all have the capacity to deal with the multiplex proteins that can simultaneiously exist, or move between, two or more subcellular location sites; (2) no accession number is needed for the input of a query protein even if using the “high- level” GO (gene ontology) prediction engine; (3) the functional domain information and sequential evolution information are fused into the “ab initio” sequence-based prediction engine to enhance its accuracy. In this protocol, a step- to-step guide is provided for how to use the web server predictors in the Cell-PLoc 2.0 package, which is freely accessible to the public at http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc-2/.