Title: Artificial intelligence in genomic sequence, protein structure function prediction and DNA microarrays: a survey
Authors: Athanasios V. Vasilakos, Bing Niu, Liang Liu, Wencong Lu
Addresses: Department of Electrical and Computer Engineering, National Technical University of Athens (NTUA), 15780, Athens, Greece. ' College of Life Science and School of Materials Science and Engineering, Shanghai University, Shanghai 200444, P.R. China. ' College of Life Science and School of Materials Science and Engineering, Shanghai University, Shanghai 200444, P.R. China. ' College of Life Science and School of Materials Science and Engineering, Shanghai University, Shanghai 200444, P.R. China
Abstract: Bioinformatics is conceptualising biology in terms of molecules (in the sense of physical chemistry) and applying |informatics techniques| (derived from disciplines such as applied mathematics, computer science and statistics) to understand and organise the information associated with these molecules on a large scale. In short, bioinformatics is a management information system for molecular biology and has many practical applications. Many artificial intelligence (AI) methods have been employed in the field of bioinformatics. In this paper, we will introduce the application of AI methods mainly in three fields: genomic sequence, protein structure and function prediction and DNA microarrays. AI methods surveyed in this paper cover artificial neural network, support vector machine (SVM), ensemble learning, hidden Markov model, and some other conventional method like rough set, decision tree, K-nearest neighbour.
Keywords: artificial intelligence; AI; data mining; bioinformatics; artificial neural networks; ANNs; ensemble learning; genomic sequences; protein structure; protein function prediction; DNA microarrays; support vector machine; SVM; hidden Markov modelling; rough sets; decision trees; K-nearest neighbour.
DOI: 10.1504/IJCIBSB.2009.030645
International Journal of Computational Intelligence in Bioinformatics and Systems Biology, 2009 Vol.1 No.2, pp.117 - 134
Published online: 29 Dec 2009 *
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