Open Access Open Access  Restricted Access Subscription Access

Soft Computing in Bioinformatics:Methodologies and Applications


Affiliations
1 Department of Computer Science, Krishna University, Machilipatnam, India
2 Department of Pharmaceutical Chemistry, Krishna University, Machilipatnam, India
 

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.
User
Notifications
Font Size

Abstract Views: 227

PDF Views: 4




  • Soft Computing in Bioinformatics:Methodologies and Applications

Abstract Views: 227  |  PDF Views: 4

Authors

Kiran Kumar Reddi
Department of Computer Science, Krishna University, Machilipatnam, India
M. V. Basaveswara Rao
Department of Pharmaceutical Chemistry, Krishna University, Machilipatnam, India

Abstract


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.