抽象的

Protein Structure Prediction Using Stochastic Process Probabilistic Model

Subhendu Bhusan Rout, Sarojananda Mishra

Protein Structure Prediction is the process of prediction of the three dimensional structure of a protein from its amino acid sequence. In order to develop a new drug it needs to process hug amount of data to study the behaviour of various types of genes. In recent years many techniques are being used for the protein structure prediction. Recently the Bioinformatics industry is in the fledgling condition and gaining more attention of researchers. Various Soft Computing methods like Fuzzy Logic, Artificial neural network, genetic algorithms, swarm optimization, etc are used for this purpose to distinguish, compare or process various type of data. It is always a big challenge for researchers to develop new tools and methods for the processing of data as well as development of drugs. It is also a major chapter for the recent researchers and scientists for the prediction of protein structure for the designing of drugs. Probabilistic theory can be applied to predict the structure of protein in less amount of time. This paper will proposed an idea for the prediction of protein structure using stochastic process probabilistic theory.