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Shi, J.Y., Zhang, S.W., Pan, Q., Cheng, Y.-M. and Xie, J. (2007) Prediction of Protein Subcellular Localization by Support Vector Machines Using Multi-Scale Energy and Pseudo Amino Acid Composition. Amino Acids, 33, 69-74.
https://doi.org/10.1007/s00726-006-0475-y

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• TITLE: Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences

  AUTHORS: Bin Liu, Hao Wu, Kuo-Chen Chou

  KEYWORDS: Pseudo Components, DNA Sequences, RNA Sequences, Protein Sequences

  JOURNAL NAME: Natural Science, Vol.9 No.4, April 28, 2017

  ABSTRACT: Pse-in-One 2.0 is a package of web-servers evolved from Pse-in-One (Liu, B., Liu, F., Wang, X., Chen, J. Fang, L. & Chou, K.C. Nucleic Acids Research, 2015, 43:W65-W71). In order to make it more flexible and comprehensive as suggested by many users, the updated package has incorporated 23 new pseudo component modes as well as a series of new feature analysis approaches. It is available at http://bioinformatics.hitsz.edu.cn/Pse-in-One2.0/. Moreover, to maximize the convenience of users, provided is also the stand-alone version called “Pse-in-One-Analysis”, by which users can significantly speed up the analysis of massive sequences.