A Comparative Analysis of Soft Computing Techniques for Predicting Protein 3d Structure

It is broadly recognised that the prediction and classification of protein sequences has become one of the most important research topic in present scenario. A variety of soft computing techniques including gravitational search algorithm, particle swarm optimization, act colony optimization, genetic algorithms and fuzzy logic have been implemented in order to enhance the efficiency and accuracy in various aspects of protein structure prediction. In this paper, we present extensive review on few soft computing approaches and based on this study we made a comparative analysis of all the techniques over standard structural datasets. The main motive of our study is to predict the nature and behaviour of different soft computing approaches when subjected to standard dataset for solving real time complex biological problems. The results were summarized for analytical analysis between different soft computing techniques.