Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/99855
Title: Pattern recognition methods for protein functional site prediction
Authors: Wang, Lipo.
Yang, Zheng Rong
Young, Natasha
Trudgian, Dave
Chou, Kuo-Chen
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Issue Date: 2005
Source: Yang, Z. R., Wang, L., Young, N., Trudgian, D., & Chou, K. C. (2005). Pattern recognition methods for protein functional site prediction. Current Protein & Peptide Science, 6(5), 479-491.
Series/Report no.: Current protein & peptide science
Abstract: Protein functional site prediction is closely related to drug design, hence to public health. In order to save the cost and the time spent on identifying the functional sites in sequenced proteins in biology laboratory, computer programs have been widely used for decades. Many of them are implemented using the state-of-the-art pattern recognition algorithms, including decision trees, neural networks and support vector machines. Although the success of this effort has been obvious, advanced and new algorithms are still under development for addressing some difficult issues. This review will go through the major stages in developing pattern recognition algorithms for protein functional site prediction and outline the future research directions in this important area.
URI: https://hdl.handle.net/10356/99855
http://hdl.handle.net/10220/8109
ISSN: 1389-2037
Rights: © 2005 Bentham Science Publishers.
metadata.item.grantfulltext: none
metadata.item.fulltext: No Fulltext
Appears in Collections:EEE Journal Articles

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