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- Indian Forester
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- Journal of Computational Intelligence in Bioinformatics
- Journal of Ecophysiology and Occupational Health
- Toxicology International (Formerly Indian Journal of Toxicology)
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Singh, Gurmit
- Status of Smooth Indian Otter (Lutra perspicillata) in Punjab
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Indian Forester, Vol 117, No 10 (1991), Pagination: 878-880Abstract
Three of the four species of otters occurring in Asia are reported in Punjab State. One of these, the Smooth Indian Otter is found in Harike Lake in Punjab. The lake habitat is threatened by a number of factors like excessive fishing, human encroachment and proliferation of water hyacinth. The author points to the need for further research on Indian otters to evolve an integrated programme.- A Note on Costus Oil from Kashmir Costus Roots
Abstract Views :250 |
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Indian Forester, Vol 85, No 1 (1959), Pagination: 56-57Abstract
No abstract- Bioinformatics: a New Era of Drug Design
Abstract Views :601 |
PDF Views:367
Authors
Madhu Yadav
1,
Gurmit Singh
2
Affiliations
1 Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences, (Formerly Allahabad Agricultural Institute), Allahabad – 211007, Uttar Pradesh, IN
2 Department of Computer Science, Sam Higginbottom Institute of Agriculture, Technology & Sciences, (Formerly Allahabad Agricultural Institute), Allahabad – 211007, Uttar Pradesh, IN
1 Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences, (Formerly Allahabad Agricultural Institute), Allahabad – 211007, Uttar Pradesh, IN
2 Department of Computer Science, Sam Higginbottom Institute of Agriculture, Technology & Sciences, (Formerly Allahabad Agricultural Institute), Allahabad – 211007, Uttar Pradesh, IN
Source
Indian Journal of Bioinformatics and Biotechnology, Vol 2, No 2 (2013), Pagination: 48-53Abstract
The Human Genome is fundamentally about information, and computers were essential both for the determination of the sequence and for the sequence and for the applications to biology and medicine that are already flowing from it. For the researchers focused on developing bioinformatics methods, use computer programs to make inferences from the archives of modern molecular biology, to make connection among them, and to derive useful and interesting prediction. Bioinformatics technology is used to solve complex biological questions related to metabolic pathways, genes, protein function and pharmacological/ developmental aspects of drugs and medicines.Companies invest millions of money and decades of time to develop a new drug. Bioinformatics helps to accelerate this process and make the drug more efficient and specific at the same time. It has significant advantages over traditionally expensive and time consuming "wet lab" research methods, because computational tools give the most predictive and accurate information about genes and proteins with regards to mediating aspects of drug action.Keywords
Human Genome, Drug Designing, Homology Modeling, Cheminformatics, SBDDReferences
- Arthur M.lesk.2002 Introduction to Bioinformatics. VII-X:263-266
- Bailey, D., and Brown, D. (2001). High-throughput chemistry and structure-based design: Survival of the smartest. Drug Disc Today 6, 57–59.
- Bo¨hm, H. J. (1992a). The computer program LUDI: A new method for the de novo design of enzyme inhibitors. J Comput Aided Mol Des 6, 61–78.
- Bo¨hm, H. J. (1996). Computational tools for structure-based ligand design. Prog Biophys Mol Biol 66, 197–210.
- Cynthia Gibas, Per Jamberk. 2002 Developing Bioinformatics computer skills.31-37.
- Dan E.Krane,Michael L. Raymer.2003 Fundamental Concepts of Bioinformatics.
- Darren R Flower.2002 Drug design cutting edge approaches. 1-47.
- Gordon, E. M., Barrett, R. W., Dower, W. J., Fodor, S. P. A., and Gallop, M. (1994). Applications of combinatorial technologies to drug discovery. 2. Combinatorial organic synthesis, library screening strategies, and future directions. J Med Chem 37, 1385–1401.
- Hansch, C., and Fujita, T. (1964). r–s–p analysis. A method for the correlation of biological activity and chemical structure. J Am Chem Soc 86, 1616–1626.
- Jeremy W Dale, Malcolm von Schantz.2002 From Gene to Genomes, Concepts and Application of DNA Technology.304-342.
- In-silico Structural Analysis and Protein Disorder Prediction: Implications for Structural Proteomics of Human Papilloma Virus Type-16 E7 Protein
Abstract Views :648 |
PDF Views:9
Authors
Affiliations
1 Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences Deemed to be University, Allahabad - 211007, IN
2 Department of Computer Science & Information Technology, Jacob School of Biotechnology and Bioengineering, SHIATS, Allahabad - 211007, IN
1 Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences Deemed to be University, Allahabad - 211007, IN
2 Department of Computer Science & Information Technology, Jacob School of Biotechnology and Bioengineering, SHIATS, Allahabad - 211007, IN
Source
International Journal of Biotechnology and Bioengineering Research, Vol 4, No 1 (2013), Pagination: 63-72Abstract
The aim of In-silico structural analysis and Protein disorder prediction for HPV type 16 E7 virus proteins is to solve the problem of designing vaccine against cervical cancer. The simultaneous structural analysis of E7 proteins out of 50 different HPV strains was carried out for prediction and validation, by using different bioinformatics tools such as CPH Model,TMHMM Server,DisEMBL and GlobPlot. In this CPH Model gives the template recognition, which is based on profile-profile alignment and it also create a model for HPV type 16 E7 protein sequence. The TMHMM Server gives prediction of transmembrane helices and discriminate between soluble and membrane proteins with high degree of accuracy show as graphical form. DisEMBL gives prediction of disordered/unstructured regions within a protein sequence of HPV 16 E7 protein andGlobPlot also predict theorder/globularity and disordered domain for protein sequence.Keywords
Human Papillomavirus, E6 and E7 Oncoproteins, CPH MODEL, TMHMM Server, Glob-plot, DisEMBL, Disordered Prediction Definition, Loop-Coils, Hot LoopsReferences
- Nelson P. H., K. H. Vousden, N. L. Hubbert, D. R. Lowy, J. T. Schiller (1989). HPV16 E6 and E7 Proteins Cooperate to Immortalize Human Foreskin Keratinocytes, The EMBO Journal, 8, 3905-3910.
- Contreras A., I. Martinez, E. Cruz, M. Lizano (2007). Role of HPV18 E6 in PKB Signal Transduction Pathways, BMC Cancer, 7(1), A7.
- Tungteakkhun S. S., M. Filippova, J. W. Neidigh, N. Fodor, P. J. Duerksen-Hughes (2008). The Interaction between Human Papillomavirus Type 16 and FADD is mediated by a Novel E6 Binding Domain, J Virol, 82, 9600-9614.
- Watts K. J., C. H. Thompson, T. E. Cossart, B. R. Rose (2001). Variable Oncogene Promoter Activity of Human Papillomavirus Type 16 Cervical Cancer Isolates from Australia, J Clin Microbiol, 35(5), 2009- 2014.
- Zheng Z. M., C. C. Baker (2006). Papillomavirus Genome Structure, Expression, and Post-transcriptional Regulation, Front Biosci, 11, 2286- 2302.
- Mayers G., E. Androphy (1995). The E6 Protein, Human Papillomaviruses, 1995 Compendium, Part III, 47-57.
- Munger K., A. L. Halpern (1997). HPV16 E7: Primary structure and biological properties. In Human Papillomaviruses 1997 Compendium, Part III, 17-36.
- Hiller T., S. Poppelreuther, F. Stubenrauch, T. Iftner (2006). Comparative Analysis of 19 Genital Human Papillomavirus Types with Regard to p53 Degradation, Immortalization, Phylogeny, and Epidemiologic Risk Classification, Cancer Epidem Biomark Prevent, 15, 1262-1267.
- Lowy D. R., D. Solomon, A. Hildesheim, J. T. Schiller, M. Schiff man (2008). Human papillomavirus Infection and the Primary and Secondary prevention of Cervical Cancer, Cancer, 113(7), 1980-1993.
- Rosty C., M. Sheffer, D. Tsafrir, N. Stransky, I. Tsafrir, M. Peter, P. Rochefordière, R. Salmon, T. Dorval, J. Thiery, J. Couturier, F. Radvanyi, E. Domany, X. Sastre-Garau (2005). Identification of a Proliferation Gene Cluster Associated with HPV E6/E7 Expression Level and Viral DNA Load in Invasive Cervical Carcinoma, Oncogene, 24(47), 7094-7104.
- Xuemei J. I., E. M. Sturgis, C. Zhao, C. J. Etzel, Q. Wei, G. Li (2009). Association of p73G4C14-to-A4T14 Polymorphism with Human Papillomavirus Type 16 Status in Squamous Cell Carcinoma of the Head and Neck in Non-Hispanic whites, Cancer, 115(8), 1660-1668.
- Nielsen M., Lundegaard C., Lund O., Petersen TN. CPHmodels-3.0 - Remote homology modelling using structure guided sequence profiles Nucleic Acids Research, 2010, Vol. 38, doi:10.1093/nar/gkq535.
- O. Lund, M. Nielsen, C. Lundegaard, P. Worning. CPH models 2.0: X3M a Computer Program to extract 3D Models. Abstract at the CASP5 conferenceA102, 2002.
- Garner, E., Romero, P., Dunker, A. K., Brown, C., and Obradovic, Z. (1999). Predicting binding regions within disordered proteins. Genome Inform. Ser. Workshop Genome Inform. , 10:41-50.
- Gunasegaram, K., Tsai, C., Kumar, S., Zanuy, D., and Nussinov, R. (2003). Extended disordered proteins: targeting function with less scaffold. Trends Biochem. Sci., 28:81-85.
- Evans, P. R. and Owen, D. J. (2002). Endocytosis and vesicle trafficking. Curr. Opin. Struct. Biol., 12:814-821.
- Schweers, O., Schonbrunn-Hanebeck, E., Marx, A., and Mandelkow, E. (1994). Structural studies of tau protein and Alzheimer paired helical filaments show no evidence for beta-structure. J. Biol. Chem., 269:24290- 24297.
- Gunasekaran, K., Tsai, C., Kumar, S., Zanuy, D., and Nussinov, R. (2003). Extended disordered proteins: targeting function with less scaffold. Trends Biochem. Sci., 28:81-85.
- Rune Linding, Robert B. Russell, Victor Neduva and Toby J. Gibson. GlobPlot: exploring protein sequences for globularity and disorder. Nucleic Acids Research Volume 31, Issue 13Pp. 3701-3708.
- Eddy, S. (1998) Profile hidden Markov models. Bioinformatics, 14, 755– 763.
- Comparative Homology Modelling for HPV Type 16 E 7 Proteins by using MODELLER and its Validations with SAVS and ProSA Web Server
Abstract Views :625 |
PDF Views:0
Authors
Affiliations
1 Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences Deemed to be University, Allahabad - 211007, IN
2 Department of Computer Science & Information Technology, SHIATS, Allahabad - 211007, IN
1 Department of Computational Biology & Bioinformatics, Sam Higginbottom Institute of Agriculture, Technology & Sciences Deemed to be University, Allahabad - 211007, IN
2 Department of Computer Science & Information Technology, SHIATS, Allahabad - 211007, IN
Source
Journal of Computational Intelligence in Bioinformatics, Vol 6, No 1 (2013), Pagination: 27-33Abstract
Human papillomaviruses (HPV) are a group of viruses which are associated with various proliferative diseases in the infected epithelium. HPV types 6, 11, 16, and 18 are the most common, are associated with lesions in the anogenital tract. The "benign" types 6 and 11 are mainly associated with condylomata acuminate of the oncogenic HPV types, HPV-16 is most frequently found in cervical carcinomas. The 3-dimentional structure of the protein was not yet available in Protein Data Bank; hence the present paper of predicting the 3D model of the HPV Type 16 E7 proteins. Template based homology modelling predicts the three-dimensional structure of hpv type 16 E 7 protein sequence (target) based primarily on its alignment to one or more proteins of known structure as template generated by MODELLER. The prediction process consists of target-template alignment, model building, and model evaluation. The model was checked for stereo chemical quality by PROCHECK, VERIFY 3D, WHAT IF, ERRAT AND ProSA servers were also used for the display of Z-scores and energy plots. Finally the protein was visualized with Swiss-PDB viewer.Keywords
Homology Modelling, SAVS, ProSA Servers, Human Papilloma VirusReferences
- Tremonton, A. and Morea, V. (2003) Assessment of homology-based predictions in CASP5. Proteins, 53 (Suppl. 6), 352–368.
- Pfister H. Biology and biochemistry of papillomaviruses. Rev Physiol Biochem Pharmacol 1984; 99: 112-81.
- Pfister H. Human papillomaviruses and genital cancer. Adv Cancer Res 1987; 48:113-47
- Cullen AP, Reid R, Campion M, Lorincz AT. Analysis of The physical state of different human papillomavirus DNAs in intra-epithelial an invasive cervical neoplasm. J Viro1991; 65:606-12.
- Pfister H. Human papillomaviruses and genital cancer. Adv CancerRes 1987; 48:113-47.
- Cullen AP, Reid R, Campion M, Lorincz AT. Analysis of The physical state of different human papillomaviruses DNAs in intraepithelial an invasive cervical neoplasm. J Viro1991; 65:606-12.
- Yee C, Krishnan-Hewlett I, Baker CC, Schlegel R, Howley PM. Presence and expression of human papillomaviruses sequences in human cervical carcinoma cell lines. Am Pathol 1985; 119:361-6.
- Van den Brule AJ, Cromme FV, Snijders PJ, Smit L, Oudejans CB, Baak JP, et al. Nonradioactive RNA in situ hybridization detection of human papillomaviruses 16-E7.
- N. Eswar, M. A. Marti-Renom, B. Webb, M. S. Madhusudhan, D. Eramian, M. Shen, U. Pieper, A. Sali. Comparative Protein Structure Modelling With MODELLER. Current Protocols in Bioinformatics, John Wiley & Sons, Inc., Supplement 15, 5.6.1-5.6.30, 2006.
- M.A. Marti-Renom, A. Stuart, A. Fiser, R. Sanchez, F. Melo, A. Sali. Comparative protein structure modelling of genes and genomes. Annu. Rev. Biophys. Biomol. Struct. 29, 291-325, 2000.
- A. Sali & T.L. Blundell. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234, 779-815, 1993.
- A. Fiser, R.K. Do & A. Sali. Modelling of loops in protein structures, Protein Science 9. 1753-1773, 2000.
- Laskowski R A, MacArthur M W, Moss D S and Thornton J M (1993). PROCHECK: a program to check the stereo chemical quality of protein structures. J. Appl. Cryst., 26, 283-291.
- WHAT IF: a molecular modelling and drug design program, G.Vriend, J. Mol. Graph. 8, 52—56 (1990).
- WHAT_CHECK (verification routines from WHAT IF) R.W.W.Hooft, G.Vriend, C.Sander and E.E. Abola, Errors in protein structures .Nature 381, 272 (1996).
- Ramachandran plot: G.N.Ramachandran, C.Ramakrishnan and V.Sasisekharan, Stereochemistry of Polypeptide Chain Conformations. J. Mol. Biol. 7, 95--99 (1963).
- Sippl, M.J. (1993), Recognition of Errors in Three-Dimensional Structures of Proteins. Proteins 17, 355-362.
- Colovos C & Yeates TO, Protein Sci. 1993 2: 1511 [PMID: 8401235]
- VERIFY3D: assessment of protein models with three-dimensional profiles: Eisenberg D, Lüthy R, Bowie JU.Source Laboratory of Structural Biology and Molecular Medicine, University of California, Los Angeles 90095, USA. [PMID: 9379925].
- Pontius J, Richelle J, Wodak SJ. (1996). Deviations from standard atomic volumes as a quality measure for protein crystal structures. J. Mol. Biol. 264, 121-136.
- Wildenstein & Sippl (2007), ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Research 35, W407-W410.
- Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994 Nov 11; 22(22):4673-80.
- Database Management System for Prediction and Management of Occupational Health Hazards
Abstract Views :269 |
PDF Views:149
Authors
Umesh Prasad
1,
Gurmit Singh
2
Affiliations
1 Isabella Thoburn College, Lucknow, U.P., IN
2 Department of Computer Science and Information Technology, Sam Higginbottom Institute of Agriculture, Technology and Sciences, Allahabad, U.P., IN
1 Isabella Thoburn College, Lucknow, U.P., IN
2 Department of Computer Science and Information Technology, Sam Higginbottom Institute of Agriculture, Technology and Sciences, Allahabad, U.P., IN
Source
Journal of Ecophysiology and Occupational Health, Vol 12, No 1-2 (2012), Pagination: 77-84Abstract
The new paradigm envisioned for epidemiological studies in 21st century advocates shifting from the current survey based protocols to combination of evidence based laboratory/ clinical studies coupled with in silico approaches. One among the key strategies is to adopt an integrated approach, which can acquire, analyze, and interpret the data both qualitative and quantitatively in one go. But, this challenging task has highly hampered due to complexity of human physiological systems, ethical dubious, etc. Thus, the present investigations were aimed to develop an interactive online tool for prediction and management of human health for Indian population engaged in different occupation. At first step, a comprehensive questionnaire on human health risk assessment and management was developed and used for offline data collection. Simultaneously, a database management system (DBMS) was developed using software and programming languages mainly including MySQL, MS Office 2007, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), Macromedia Dreamweaver, SPSS, java script, C++ language, Microsoft DOT NET, etc. For the purpose, the DBMS was developed and is being used through website "www.healthriskindia.in" for online survey. Upon the analysis of data collected from 2000 individuals of Jhansi and Lucknow districts of Uttar Pradesh, the socioeconomic status, education, hygiene status, occupation type, etc. were found to be associated with proneness to the diseases. Further, the relation between health status and day to day activities of the individuals engaged in different occupations of different groups in the society was analyzed successfully using DBMS. The analysis made in different combination of permutation using the data of 2000 volunteers show significant simulation with epidemiological data generated through conventional means for the mimicking population residing in the study area.Keywords
In silico, DBMS, Health, Risk.- A Dynamic Human Health Risk Assessment System
Abstract Views :281 |
PDF Views:0
Authors
Affiliations
1 Central Library, Isabella Thoburn College, Lucknow, IN
2 Department of Computer Science and Information Technology, Sam Higginbottom Institute of Agriculture, Technology and Sciences, Allahabad, IN
3 In Vitro Toxicology, Indian Institute of Toxicology Research, Post Box 80, Lucknow, Uttar Pradesh, IN
1 Central Library, Isabella Thoburn College, Lucknow, IN
2 Department of Computer Science and Information Technology, Sam Higginbottom Institute of Agriculture, Technology and Sciences, Allahabad, IN
3 In Vitro Toxicology, Indian Institute of Toxicology Research, Post Box 80, Lucknow, Uttar Pradesh, IN