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Shen, H.B. and Chou, K.C. (2005) Using optimized evi-dence-theoretic K-nearest neighbor classifier and pseudo amino acid composition to predict membrane protein types. Biochemical & Biophysical Research Communica-tions, 334, 288-292.

has been cited by the following article:

• TITLE: REVIEW : Recent advances in developing web-servers for predicting protein attributes

  AUTHORS: Kuo-Chen Chou, Hong-Bin Shen

  KEYWORDS: Cell-PLoc; Signal-CF; Signal-3L; MemType-2L; EzyPred; HIVcleave; GPCR-CA;ProtIdent; QuatIdent; FoldRate

  JOURNAL NAME: Natural Science, Vol.1 No.2, September 28, 2009

  ABSTRACT: Recent advance in large-scale genome se-quencing has generated a huge volume of pro-tein sequences. In order to timely utilize the in-formation hidden in these newly discovered sequences, it is highly desired to develop com- putational methods for efficiently identifying their various attributes because the information thus obtained will be very useful for both basic research and drug development. Particularly, it would be even more useful and welcome if a user-friendly web-server could be provided for each of these methods. In this minireview, a sy- stematic introduction is presented to highlight the development of these web-servers by our group during the last three years.