Title |
EXPLORATION OF SCHIZOPHRENIA: A NEUROLOGICAL DISORDER USING BIOINFORMATICS TOOLS AND TECHNIQUES |
| Int J Comput Biol Vol:1 Iss:1 (2010-06-15) : 1-3 |
Authors |
Bajaj N.J., Chitlange N.R., Shaikh Ubed, Sanjaykumar Chaubey, Gomase V.S. |
Published on |
15 Jun 2010 Pages : 1-3 Article Id : BIA0001604 Views : 983 Downloads : 985 |
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Abstract |
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Schizophrenia is one of the most confusing and disabling mental illness that makes it difficult to tell the difference between real and unreal experiences, to think logically, to have normal emotional responses, and to behave normally in social situations. Schizophrenia may occur due to environmental as well as the genetic factor. COMT is one of the genes
responsible for Schizophrenia. We predicted the active site of COMT gene and its complementary ligand structures. This complementary ligand binds to the active site of the gene COMT. Binding ability of ligand to the COMT is important in drug design for curing Schizophrenia.
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Title |
SUPPORT VECTOR MACHINE (SVM) BASED PREDICTION OF PROMISCUOUS MHC CLASS BINDING PEPTIDES |
| Int J Comput Biol Vol:1 Iss:1 (2010-06-15) : 4-8 |
Authors |
Gomase V.S., Chitlange N.R. |
Published on |
15 Jun 2010 Pages : 4-8 Article Id : BIA0001605 Views : 992 Downloads : 860 |
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Shigella flexneri is a species of Gram-negative bacteria in the genus Shigella that can cause diarrhea in humans. Peptide fragments of antigen protein can be used to select nonamers for use in rational vaccine design and to increase the understanding of roles of the immune system in infectious diseases. Analysis shows MHC class II binding peptides of antigen protein from Shigella flexneri are important determinant for protection of host form parasitic infection. In this assay, we used PSSM and SVM algorithms for antigen design and predicted the binding affinity of antigen protein having 574 amino acids, which shows 566 nonamers. Binding ability prediction of antigen peptides to major histocompatibility complex (MHC) class I & II molecules is important in vaccine development from Shigella flexneri.
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Title |
APPLICATION COMPUTATIONAL INTELLIGENCE FOR DEVELOPMENT OF SYNTHETIC PEPTIDE VACCINE FROM MYCOBACTERIUM AVIUM |
| Int J Comput Biol Vol:1 Iss:1 (2010-06-15) : 9-13 |
Authors |
Gomase V.S., Chitlange N.R. |
Published on |
15 Jun 2010 Pages : 9-13 Article Id : BIA0001606 Views : 1028 Downloads : 1036 |
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Abstract |
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Mycobacterium avium causes MAC diseases. Symptoms of MAC diseases are reminiscent of tuberculosis; they include fever, fatigue, and weight loss. Peptide fragments of antigen protein can be used to select nonamers for use in rational vaccine design and to increase the understanding of roles of the immune system in infectious diseases. Analysis shows MHC class II binding peptides of antigen protein from Mycobacterium avium are important determinant for protection of host form bacterial infection. In this assay, we used PSSM and SVM algorithms for antigen design and predicted the binding affinity of antigen protein having 195 amino acids, which shows 187 nonamers. Binding ability prediction of antigen peptides to major histocompatibility complex (MHC) class I & II molecules is important in vaccine development from Mycobacterium avium.
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