DOI QR코드

DOI QR Code

Bioinformatics in the Post-genome Era

  • Yu, Ung-Sik (National Genome Information Center, Korea Research Institute of Bioscience & Biotechnology) ;
  • Lee, Sung-Hoon (National Genome Information Center, Korea Research Institute of Bioscience & Biotechnology) ;
  • Kim, Young-Joo (National Genome Information Center, Korea Research Institute of Bioscience & Biotechnology) ;
  • Kim, Sang-Soo (National Genome Information Center, Korea Research Institute of Bioscience & Biotechnology)
  • Published : 2004.01.31

Abstract

Recent years saw a dramatic increase in genomic and proteomic data in public archives. Now with the complete genome sequences of human and other species in hand, detailed analyses of the genome sequences will undoubtedly improve our understanding of biological systems and at the same time require sophisticated bioinformatic tools. Here we review what computational challenges are ahead and what are the new exciting developments in this exciting field.

Keywords

References

  1. Bateman, A., Birney, E., Cerruti, L., Durbin, R., Etwiller, L., Eddy, S. R., Griffiths-Jones, S., Howe, K. L., Marshall, M. and Sonnhammer, E. L. (2002) The Pfam Protein Families Database. Nucleic Acids Res. 30, 276-280. Pfam (http://www.sanger.ac.uk/Software/Pfam/) https://doi.org/10.1093/nar/30.1.276
  2. Borman, S. (2003) Divining protein architecture. Chemical & Engineering News 81, 26-30. (http://pubs.acs.org/isubscribe/journals/cen/81/i31/html/8131sci1.html)
  3. CHI Conference (2003) Molecular Medicine Marketplace in Santa Clara, CA, USA. (http://www.bio-itworld.com/news/050903_report2511.html)
  4. Collins, F. S., Green, E. D., Guttmacher, A. E. and Guyer, M. S. (2003) A vision for the future of genomics research. Nature 422, 835-847. https://doi.org/10.1038/nature01626
  5. Dahlquist, K. D., Salomonis, N., Vranizan, K., Lawlor, S. C. and Conklin, B. R. (2002) GenMAPP, a new tool for viewing and analyzing microarray data on biological pathways. Nature Genetics 31, 19-20. Gene MicroArray Pathway Profiler (http://www.genmapp.org/) https://doi.org/10.1038/ng0502-19
  6. Davidson, E. (2003) Abstract from Transcriptome 2003 in Tokyo, Japan.
  7. Gojobori, T. and the H-Invitational team (2003) Abstract from Transcriptome 2003 in Tokyo, Japan.
  8. Hood, L. (2003) Abstract from Transcriptome 2003 in Tokyo, Japan.
  9. International Human Genome Sequencing Consortium (2001) Initial sequencing and analysis of the human genome. Nature 409, 860-921. https://doi.org/10.1038/35057062
  10. Kanehisa, M., Goto, S., Kawashima, S. and Nakaya, A. (2002) The KEGG databases at GenomeNet. Nucleic Acids Res. 30, 42-46. Kyoto Encyclopedia of Genes and Genomes (http://www.genome.ad.jp/kegg) https://doi.org/10.1093/nar/30.1.42
  11. Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M. and Haussler, D. (2002) The Human Genome Browser at UCSC. Genome Res. 12, 996-1006. UCSC Genome Browser (http://genome.ucsc.edu) https://doi.org/10.1101/gr.229102.ArticlepublishedonlinebeforeprintinMay2002
  12. Khatri, P., Draghici, S., Ostermeier, G. C. and Krawetz, S. A. (2002) Profiling gene expression using onto-express. Genomics 79, 266-270. Onto-Express (http://vortex.cs.wayne.edu/Projects.html) https://doi.org/10.1006/geno.2002.6698
  13. Korf, I., Flicek, P., Duan, D. and Brent, M. R. (2001) Integrating genomic homology into gene structure prediction. Bioinformatics 17, S140-148. https://doi.org/10.1093/bioinformatics/17.suppl_1.S140
  14. Sharan, R., Maron-Katz, A. and Shamir, R. (2003) CLICK and EXPANDER: A System for Clustering and Visualizing Gene Expression Data. Bioinformatics 19, 1787-1799. https://doi.org/10.1093/bioinformatics/btg232
  15. Stein, L. (2002) O'Reilly's Bioinformatics Technology Conference. (http://www.oreillynet.com/pub/a/network/2002/01/29/bioday2. html)
  16. Tatusov, R. L., Natale, D. A., Garkavtsev, I. V., Tatusova, T. A., Shankavaram, U. T., Rao, B. S., Kiryutin, B., Galperin, M. Y., Fedorova, N. D. and Koonin, E. V. (2001) The COG database: new developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res. 29, 22-28. Clusters of Orthologous Groups (http://www.ncbi.nih.gov/COG/) https://doi.org/10.1093/nar/29.1.22
  17. The FANTOM Consortium and the RIKEN Genome Exploration Research Group Phase I & II Team (2002) Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature 420, 563-573. https://doi.org/10.1038/nature01266
  18. The Gene Ontology Consortium (2001) Creating the gene ontology resource: design and implementation. Genome Res. 11, 1425-1433. Gene Ontology Consortium (http://www.geneontology.org) https://doi.org/10.1101/gr.180801
  19. The 5th Critical Assessment of Structure Prediction Methods (2003) (http://predictioncenter.llnl.gov/casp5/Casp5.html)
  20. Uhlen, M. (2003) Abstract from Transcriptome 2003 in Tokyo, Japan.
  21. Wolfsberg, T. G., Wetterstrand, K. A., Guyer, M. S., Collins, F. S. and Baxevanis, A. D. (2002) A user's guide to the human genome. Nat. Genet. 32, Suppl. 1-79. https://doi.org/10.1038/ng961
  22. Zhang, M. Q. (2003) Abstract from Transcriptome 2003 in Tokyo, Japan.

Cited by

  1. Functional screening for proapoptotic genes by reverse transfection cell array technology vol.87, pp.5, 2006, https://doi.org/10.1016/j.ygeno.2005.12.009
  2. Molecular Pathology Informatics vol.36, pp.1, 2016, https://doi.org/10.1016/j.cll.2015.09.007
  3. Ecotoxicogenomics: linkages between exposure and effects in assessing risks of aquatic contaminants to fish vol.19, pp.3, 2005, https://doi.org/10.1016/j.reprotox.2004.06.007
  4. Applications of Bioinformatics in Cancer Detection: A Lexicon of Bioinformatics Terms vol.1020, pp.1, 2004, https://doi.org/10.1196/annals.1310.021
  5. Bioinformatics and molecular modeling in glycobiology vol.67, pp.16, 2010, https://doi.org/10.1007/s00018-010-0352-4
  6. Structural bioinformatics in post-genomic era vol.20, pp.1-2, 2004, https://doi.org/10.7124/bc.000695
  7. Molecular Pathology Informatics vol.8, pp.2, 2015, https://doi.org/10.1016/j.path.2015.02.013
  8. Utilization of multiple “omics” studies in microbial pathogeny for microbiology insights vol.3, pp.4, 2013, https://doi.org/10.1016/S2221-1691(13)60073-8
  9. Role of remote sensing, geographic bioinformatics system and bioinformatics in kala-azar epidemiology vol.25, pp.6, 2011, https://doi.org/10.1016/S1674-8301(11)60050-X
  10. Prospecting the past: genetic perspectives on the extinction and survival of indigenous peoples of the Caribbean vol.33, pp.1, 2014, https://doi.org/10.1080/14636778.2013.873245
  11. Highly Sensitive MALDI Analyses of Glycans by a New Aminoquinoline-Labeling Method Using 3-Aminoquinoline/α-Cyano-4-hydroxycinnamic Acid Liquid Matrix vol.83, pp.10, 2011, https://doi.org/10.1021/ac103203v
  12. Genome data mining for everyone vol.41, pp.11, 2008, https://doi.org/10.5483/BMBRep.2008.41.11.757
  13. A survey of tools for analysing DNA fingerprints 2015, https://doi.org/10.1093/bib/bbv016
  14. Genome Sequencing and Identification of Gene Function in Rice vol.33, pp.8, 2006, https://doi.org/10.1016/S0379-4172(06)60098-X