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Soft Computing in Bioinformatics:Methodologies and Applications
Bioinformatics, an area that has evolved in response to this deluge of information, can be viewed as the use of computational methods to handle biological data. It is an interdisciplinary field involving biology, computer science, mathematics and statistics to analyze biological sequence data, genome content & arrangement, and to predict the function and structure of macromolecules. Soft computing is a consortium of methodologies that work synergistically and provide, in one form or another, flexible information processing capabilities for handling real life ambiguous situations. Its aim, unlike conventional (hard) computing, is to exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to achieve tractability, robustness, low solution cost, and close resemblance with human like decision-making. The paper will focus on soft computing paradigm in bioinformatics with particular emphasis on research.
Keywords
Bioinformatics, Soft Computing Paradigm, Ant Colony Optimization, Bioinformatics Algorithms, Tabu Search, Support Vector Machines.
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