Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification

IEEE Transactions on Nanobioscience
Chuen-Der HuangNikhil R Pal

Abstract

The structure classification of proteins plays a very important role in bioinformatics, since the relationships and characteristics among those known proteins can be exploited to predict the structure of new proteins. The success of a classification system depends heavily on two things: the tools being used and the features considered. For the bioinformatics applications, the role of appropriate features has not been paid adequate importance. In this investigation we use three novel ideas for multiclass protein fold classification. First, we use the gating neural network, where each input node is associated with a gate. This network can select important features in an online manner when the learning goes on. At the beginning of the training, all gates are almost closed, i.e., no feature is allowed to enter the network. Through the training, gates corresponding to good features are completely opened while gates corresponding to bad features are closed more tightly, and some gates may be partially open. The second novel idea is to use a hierarchical learning architecture (HLA). The classifier in the first level of HLA classifies the protein features into four major classes: all alpha, all beta, alpha + beta, and alpha/beta. And i...Continue Reading

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Citations

Aug 13, 2013·Computers in Biology and Medicine·Elham AbbasiM E Shiri
Sep 29, 2005·Bioinformatics·Huzefa Rangwala, George Karypis
Sep 29, 2009·Journal of Bioinformatics and Computational Biology·Peng ChenClay Gloster
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Jun 24, 2014·TheScientificWorldJournal·Yessi JusmanNoor Azuan Abu Osman
Mar 24, 2010·Journal of Theoretical Biology·Loris NanniAlessandra Lumini
Dec 23, 2014·IEEE Transactions on Neural Networks and Learning Systems·Rudrasis Chakraborty, Nikhil R Pal
Jul 22, 2014·Proteins·S M Saberi FathiJack A Tuszynski
May 1, 2014·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Abdollah DehzangiAbdul Sattar
Aug 19, 2007·IEEE Transactions on Nanobioscience·Ken-Li LinD Frank Hsu
Jul 23, 2009·IEEE Engineering in Medicine and Biology Magazine : the Quarterly Magazine of the Engineering in Medicine & Biology Society·Ken-Li LinSudeepta Ojha
Jan 27, 2011·IEEE Transactions on Nanobioscience·Ken-Li LinNikhil R Pal
Jul 17, 2014·TheScientificWorldJournal·Loris NanniSheryl Brahnam
Oct 4, 2014·Journal of Theoretical Biology·Reza Zohouri Aram, Nasrollah Moghadam Charkari
May 4, 2013·Evolutionary Bioinformatics Online·Chiou-Yi HorHung-Hsin Chen
Oct 28, 2015·Journal of Computational Chemistry·Ngaam J CheungHong-Bin Shen

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