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Computational Intelligence and Pattern Analysis in Biological Informatics by Jason T. Wang, Sanghamitra Bandyopadhyay, Ujjwal Maulik

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Preface

Computational biology is an interdisciplinary field devoted to the interpretation and analysis of biological data using computational techniques. It is an area of active research involving biology, computer science, statistics, and mathematics to analyze biological sequence data, genome content and arrangement, and to predict the function and structure of macromolecules. This field is a constantly emerging one, with new techniques and results being reported every day. Advancement of data collection techniques is also throwing up novel challenges for the algorithm designers to analyze the complex and voluminous data. It has already been established that traditional computing methods are limited in their scope for application to such complex, large, multidimensional, and inherently noisy data. Computational intelligence techniques, which combine elements of learning, adaptation, evolution, and logic, are found to be particularly well suited to many of the problems arising in biology as they have flexible information processing capabilities for handling huge volume of real-life data with noise, ambiguity, missing values, and so on. Solving problems in biological informatics often involves search for some useful regularities or patterns in large amounts of data that are typically characterized by high dimensionality and low sample size. This necessitates the development of advanced pattern analysis approaches since the traditional methods often become intractable in such situations. ...

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