Computational Mining of Genomic and Proteomic Data to Gain Insight for Alzheimers Disease AD

Abstract

The principal title of this work is the identification of important genes and proteins with their role involved in AD and their interaction studies. In the first chapter a general background is presented, Detail literature about disease, its risk factors, epidemiology, and genetics of disease, also overview the problem statement, scope, significance of the study and limitation of the study. newlineIn the Second, Third, Fourth and Fifth chapters discussed about four different objectives, their methodology, results, conclusions in form of major finding and discussion about their applications in finding potential biomarkers for confirmation of AD. In the Seventh chapter summarizes the conclusions of the key reports of the study and discusses prospects for further work in these areas. In summary, the present study has made an attempt to show how applications of different computational and statistical tools help in finding useful knowledge about pathogenetic mechanism of AD. Through structure data of Proteins about different inhibitors enlightened our knowledge about their binding energy and inhibitory potential. This study can useful to generate new biological information. With the exponential growth of sequence and structure data, Bioinformatics can still play a very important role in new biological discovery and in formulating intelligent questions for designing experiments. newline newline