Computational Intelligence in Bioinformatics
نویسنده
چکیده
Copyright: © 2014 Nebel JC. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Since the term ‘bioinformatics’ was coined in 1970 [1], the field of bioinformatics has become relatively mature allowing high-throughput whole genome sequencing and making computer-aided drug design an essential part of drug discovery. With the needs of addressing ever more complex problems in a faster and more accurate manner, the bioinformatics community has exploited many different paradigms. Among them, ‘Computational Intelligence’ has proved particularly effective since nature-inspired computational approaches are able to extract patterns from large volumes of data, infer rules from sets of examples and adapt according to changing data and/or contexts [2]. Many of those methods have been applied to bioinformatics; they include: Artificial Immune Systems [3], Bayesian Networks [4], Evolutionary Algorithms [5], Fuzzy Logic [6], Hidden Markov Models [7], Neural Networks [8], Rough Sets [9], Support Vector Machines (SVM) [10] and Swarm Intelligence [11]. In this special issue, we present six papers that illustrate the latest applications of Computational Intelligence in Bioinformatics.
منابع مشابه
Computational Intelligence in Biomedicine and Bioinformatics, Current Trends and Applications
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