Abstract
The emergence of bioinformatics has enriched the different dimensions of biological research. A sizable quantum of complex biological data can now be encapsulated into a more palatable form particularly in the context of human health. We provide a critical overview on such bioinformatic databases and softwares that enable a deeper insight into the human genome and proteome.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Adams MD, et al. The genome sequence of Drosophila melanogaster. Science. 2000;287(5461):2185–95.
Aloy P, Russell RB. Ten thousand domain-domain interactions for the molecular biologist. Nat Biotechnol. 2004;22(10):1317–21.
Altshuler D, et al. An SNP map of the human genome generated by reduced representation shotgun sequencing. Nature. 2000;407(6803):513–6.
Bartel PL, Fields S (eds). The yeast two-hybrid system. In: Bartel PL, Fields S, editors, Advances in molecular biology. New York: Oxford University Press; 1997.
Blackstock WP, Weir MP. Proteomics: quantitative and physical mapping of cellular proteins. Trends Biotechnol. 1999;17(3):121–7.
Bult CJ, et al. Complete genome sequence of the methanogenic archaeon, Methanococcus jannaschii. Science. 1996;273(5278):1058–73.
C. elegans Sequencing Consortium. Genome sequence of the nematode C. elegans: a platform for investigating biology. Science. 1998;282(5396):2012–8.
Cambien F, et al. Deletion polymorphism in the gene for angiotensin-converting enzyme is a potent risk factor for myocardial infarction. Nature. 1992;359(6396):641–4.
Chakrabarti P, Janin J. Dissecting protein–protein recognition sites. Proteins. 2002;47(3):334–43.
Chanock S. Candidate genes and single nucleotide polymorphisms (SNPs) in the study of human disease. Dis Markers. 2001;17(2):89–98.
Cheng I, et al. 8q24 and prostate cancer: association with advanced disease and meta-analysis. Eur J Hum Genet. 2008;16(4):496–505.
de Bakker PI, Yelensky R, Pe’er I, Gabriel SB, Daly MJ, Altshuler D. Efficiency and power in genetic association studies. Nat Genet. 2005;37(11):1217–23.
De Jager PL, et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet. 2009;41(7):776–82.
Deng M, Mehta S, Sun F, Chen T. Inferring domain-domain interactions from protein-protein interactions. Genome Res. 2002;12:1540–8.
Dove A. Proteomics: translating genes into products? Nat Biotechnol. 1999;17(3):233–6.
Duerr RH, et al. A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science. 2006;314(5804):1461–3.
Enright AJ, Ililopoulos I, Kyrpides NC, Ouzounis CA. Protein interaction maps for complete genomes based on gene fusion events. Nature. 1999;402(6757):86–90.
Fields S, Song O. A novel genetic system to detect protein–protein interactions. Nature. 1989;340(6230):245–6.
Fleischmann RD, et al. Whole genome random sequencing and assembly of haemophilus-influenzae Rd. Science. 1995;269:496–512.
Fraser CM, et al. The minimal gene complement of mycoplasma-genitalium. Science. 1995;270(5235):397–403.
Freedman ML, et al. Admixture mapping identifies 8q24 as a prostate cancer risk locus in African–American men. Proc Natl Acad Sci USA. 2006;103(38):14068–73.
Goffeau A, et al. Life with 6000 genes. Science. 1996;274(5287):546, 563–7.
Gratacòs M, et al. A polymorphic genomic duplication on human chromosome 15 is a susceptibility factor for panic and phobic disorders. Cell. 2001;106(3):367–79.
Guimaraes KS, Jothi R, Zotenko E, Przytycka TM. Predicting domain-domain interactions using a parsimony approach. Genome Biol. 2006;7:R104.
Howard TD, et al. Gene-gene interaction in asthma: IL4RA and IL13 in a Dutch population with asthma. Am J Hum Genet. 2002;70(1):230–6.
Hunter S, et al. InterPro: the integrative protein signature database. Nucleic Acids Res. 2009;37(D):D211–5.
Ingolfsson H, Yona G. Protein domain prediction. Methods Mol Biol. 2008;426:117–43.
International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature. 2004;431(7011):931–45.
Jacques PF, et al. Relation between folate status, a common mutation in methylene tetrahydrofolate reductase, and plasma homocysteine concentrations. Circulation. 1996;93(1):7–9.
Kortemme T, Baker D. Computational design of protein–protein interactions. Curr Opin Struct Biol. 2004;8(1):91–7.
Kraft P, Cox DG. Study designs for genome-wide association studies. Adv Genet. 2008;60:465–504.
Lander ES, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409(6822):860–921.
Lee H, Deng M, Sun F, Chen T. An integrated approach to the prediction of domain-domain interactions. BMC Bioinformatics. 2006;7:269–27.
Libioulle C, et al. Novel Crohn disease locus identified by genome-wide association maps to a gene desert on 5p13.1 and modulates expression of PTGER4. PLoS Genet 2007, 3(4):e58.
LoConte L, et al. The atomic structure of protein–protein recognition sites. J Mol Biol. 1999;285(5):2177–98.
Lu L, Lu H, Skolnick J. MULTIPROSPECTOR: an algorithm for the prediction of protein-protein interactions by multimeric threading. Proteins. 2002;49(3):350–64.
Lykke-Andersen J. mRNA quality control: marking the message for life or death. Curr Biol. 2001;11(3):R88–91.
Marchler-Bauer A, et al. CDD: a Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res. 2011;39(D):D225–9.
Marcotte EM, et al. Detecting protein function and protein–protein interactions from genome sequences. Science. 1999;285(5428):751–3.
Moore JH, Asselbergs FW, Williams SM. Bioinformatics challenges for genome-wide association studies. Bioinformatics. 2010;26(4):445–55.
Mount DW, Pandey R. Using bioinformatics and genome analysis for new therapeutic interventions. Mol Cancer Ther. 2005;4(10):1636–43.
Musani SK, et al. Detection of gene x gene interactions in genome-wide association studies of human population data. Hum Hered. 2007;63(2):67–84.
Ng SK, Zhang Z, Tan SH, Lin K. InterDom: a database of putative interacting protein domains for validating predicted protein interactions and complexes. Nucleic Acids Res. 2003;31(1):251–4.
Pabinger S, Dander A, Fischer M, Snajder R, Sperk M, Efremova M, et al. A survey of tools for variant analysis of next-generation genome sequencing data. Brief Bioinform. 2014;15(2):256–78.
Panwar D, Rawal L, Ali S. Molecular docking uncovers TSPY binds more efficiently with eEF1A2 compared to eEF1A1. J Biomol Struct Dyn. 2015;33(7):1412–23.
Poort SR, Rosendaal FR, Reitsma PH, Bertina RM. A common genetic variation in the 3′-untranslated region of the prothrombin gene is associated with elevated plasma prothrombin levels and an increase in venous thrombosis. Blood. 1996;88(10):3698–703.
Reich DE, Lander ES. On the allelic spectrum of human disease. Trends Genet. 2001;17(9):502–10.
Richards RI, Holman K, Yu S, Sutherland GR. Fragile X syndrome unstable element, p(CCG)n, and other simple tandem repeat sequences are binding sites for specific nuclear proteins. Hum Mol Genet. 1993;2(9):1429–35.
Salwinski L, Eisenberg D. Computational methods of analysis of protein–protein interactions. Curr Opin Struct Biol. 2003;13(3):377–82.
Schork NJ, Murray SS, Frazer KA, Topol EJ. Common vs. rare allele hypotheses for complex diseases. Curr Opin Genet Dev. 2009;19(3):212–9.
Seng KC, Seng CK. The success of the genome-wide association approach: a brief story of a long struggle. Eur J Hum Genet. 2008;16:554–64.
Small KM, Wagoner LE, Levin AM, Kardia SL, Liggett SB. Synergistic polymorphisms of beta1- and alpha2C-adrenergic receptors and the risk of congestive heart failure. N Engl J Med. 2002;347(15):1135–42.
Ta HX, Holm L. Evaluation of different domain-based methods in protein interaction prediction. Biochem Biophys Res Commun. 2009;390(3):357–62.
Teichmann SA. Principles of protein-protein interactions. Bioinformatics. 2002;18(Suppl 2):S249.
The International HapMap Consortium. The International HapMap Project. Nature. 2003;426(6968):789–96.
Uetz P, et al. A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae. Nature. 2000;403(6770):623–7.
Valencia A, Pazos F. Computational methods for the prediction of protein interactions. Curr Opin Struct Biol. 2002;12(3):368–73.
Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al. The sequence of the human genome. Science. 2001;291:1304–51.
Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447(7145):661–78.
Competing Interests
No competing interests to be disclosed.
Dr. Leena Rawal
Dr. Leena Rawal is currently working as a scientist at the Department of Cytogenetics, Dr Lal PathLabs Limited, New Delhi. She holds a doctoral degree in molecular genetics from the National Institute of Immunology, New Delhi, and has significant years of experience in the field. Her expertise lies in the area of human and animal genetics, proteomics, gene regulation, cytogenetics, and bioinformatics. Earlier, she has headed the Molecular Diagnostics and Research Division of a renowned pharmacogenomics-based organization that provides state-of-the-art in vitro personalized diagnostic services to medical healthcare and allied communities.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Rawal, L., Panwar, D., Ali, S. (2017). Bioinformatics Databases: Implications in Human Health. In: Rawal, L., Ali, S. (eds) Genome Analysis and Human Health. Springer, Singapore. https://doi.org/10.1007/978-981-10-4298-0_6
Download citation
DOI: https://doi.org/10.1007/978-981-10-4298-0_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-4297-3
Online ISBN: 978-981-10-4298-0
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)