Beschreibung
Prediction of protein in large databases is one of the major research objectives in structural and functional proteomics. This can significantly contribute to the elucidation of functional diversity of homologous proteins. Therefore, its amino acid sequence is compared with the sequences of structural database using computational techniques. It needs to be design drugs for diseases which are being caused by proteins whose structure is unknown; every protein has some sequences of patterns which will be matched using algorithm and classify using sequences of those proteins. Experimental procedures for protein structure prediction is inherently low and are thus unable to annotate an irrelevant portion of proteins that are becoming available due to rapid advances in genome sequencing technology. This has motivated the development of computational techniques that utilize these experimental data for protein prediction. Even though, they proved on the worktable, the structure and function of a protein can be effectively predicted by computational approaches that compel the advanced experimental assays.
Autorenporträt
Dr. P. Satheesh Working as a Section Head and M.Tech Coordinator in the Department of Computer Science and Engineering at MVGR College of Engineering , Vizianagaram, Andhra Pradesh, India. He organized several National and International Conferences and Workshops in the area of Computational Intelligence and Bioinformatics.
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