Bioinformatics: the machine learning approach
Bioinformatics: the machine learning approach
Neutral Networks in Optimization
Neutral Networks in Optimization
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Evaluating Protein Similarity from Coarse Structures
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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One of the central problems in functional genomics is to establish the classification schemes of protein structures. In this paper the relationship of protein structures is uncovered within the framework of supervised learning. Specifically, the novel patterns based on convex hull representation are firstly extracted from a protein structure, then the classification system is constructed and machine learning methods such as neural networks, Hidden Markov Models (HMM) and Support Vector Machines (SVMs) are applied. The CATH scheme is highlighted in the classification experiments. The results indicate that the proposed supervised classification scheme is effective and efficient.