The emerging in-silico scientist: How text-based bioinformatics is bridging biology and artificial intelligence

IEEE Engineering in Medicine and Biology Magazine

Volumn 23, Issue 2, 2004, Pages 87-93

  Wren, Jonathan D ^a  

^a UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; COMPUTER PROGRAM; INFORMATION PROCESSING; MEDLINE; PROBLEM SOLVING; RESOURCE ALLOCATION; REVIEW;

ABSTRACTING AND INDEXING; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOLOGY; COMPUTATIONAL BIOLOGY; DATABASE MANAGEMENT SYSTEMS; DATABASES, BIBLIOGRAPHIC; GENOMICS; INFORMATION STORAGE AND RETRIEVAL; NATURAL LANGUAGE PROCESSING; PERIODICALS; VOCABULARY, CONTROLLED;

EID: 3042765617     PISSN: 07395175     EISSN: None     Source Type: Journal    
DOI: 10.1109/MEMB.2004.1310989     Document Type: Review

References (38)

1. C. Blaschke, L. Hirschman, and A. Valencia, "Information extraction in molecular biology," Brief Bioinform., vol. 3, pp. 154-165, 2002.
2. B. de Bruijn and J. Martin, "Getting to the (c)ore of knowledge: Mining biomedical literature," Int. J. Med. Inf., vol. 67, pp. 7-18, 2002.
3. L. Hirschman, J.C. Park, J. Tsujii, L. Wong, and C.H. Wu, "Accomplishments and challenges in literature data mining for biology," Bioinformatics, vol. 18, pp. 1553-1561, 2002.
4. R. Mack and M. Hehenberger, "Text-based knowledge discovery: Search and mining of life-sciences documents," Drug. Discov. Today, vol. 7, pp. 89-98, 2002.
5. P.M. Nadkarni, "An introduction to information retrieval: Applications in genomics," Pharmacogenomics J., vol. 2, pp. 96-102, 2002.
6. M. Hearst, "Untangling text data mining," presented at 1999 Proceedings of the Association for Computational Linguistics: College Park, Maryland.
7. N. Ge, J. Hale, and E. Charniak, "A statistical approach to anaphora resolution," presented at Proc. of the Sixth Workshop on Very Large Corpora,Montreal, Quebec, 1998.
8. A. Hamosh, A.F. Scott, J. Amberger, C. Bocchini, D. Valle, and V.A. McKusick, "Online Mendelian inheritance in man (OMIM), A knowledgebase of human genes and genetic disorders," Nucleic Acids Res., vol. 30, pp. 52-55, 2002.
9. I. Xenarios, L. Salwinski, X.J. Duan, P. Higney, S.M. Kim, and D. Eisenberg, "DIP, the database of interacting proteins: A research tool for studying cellular networks of protein interactions," Nucleic Acids Res., vol. 30, pp. 303-305, 2002.
10. C. Blaschke and A. Valencia, "The potential use of SUISEKI as a protein interaction discovery tool," Genome Inform. Ser. Workshop Genome Inform., vol. 12, pp. 123-134, 2001.
11. L. Wong, "PIES, a protein interaction extraction system," Pac. Symp. Biocomput., pp. 520-531, 2001.
12. R. Gaizauskas, G. Demetriou, P.J. Artymiuk, and P. Willett, "Protein structures and information extraction from biological texts: The PASTA system," Bioinformatics, vol. 19, pp. 135-143, 2003.
13. J.D. Wren and H.R. Garner, "Heuristics for identification of acronym-definition patterns within text: Towards an automated construction of comprehensive acronym-definition dictionaries," Methods Informat. Med., vol. 41, pp. 426-434, 2002.
14. J. Pustejovsky, J. Castano, B. Cochran, M. Kotecki, and M. Morrell, "Automatic extraction of acronym-meaning pairs from MEDLINE databases," Medinfo., vol. 10, pp. 371-375, 2001.
15. J.T. Chang, H. Schutze, and R.B. Altman, "Creating an online dictionary of abbreviations from MEDLINE," J. Amer. Med. Inform. Assoc., vol. 9, pp. 612-620, 2002.
16. P.K. Shah, C. Perez-Iratxeta, P. Bork, and M.A. Andrade, "Information extraction from full text scientific articles: Where are the keywords?," BMC Bioinformatics, vol. 4, p. 20, 2003.
17. J.D. Wren, R. Bekeredjian, J.A. Stewart, R.V. Shohet, and H.R. Garner, "Knowledge discovery by automated identification and ranking of implicit relationships," Bioinformatics, vol. 20, pp. 389-398, 2004.
18. H. Pearson, "Biology's name game," Nature, vol. 411, pp. 631-632, 2001.
19. J.H. Chiang and H.C. Yu, "MeKE: Discovering the functions of gene products from biomedical literature via sentence alignment," Bioinformatics, vol. 19, pp. 1417-1422, 2003.
20. T.K. Jenssen, A. Laegreid, J. Komorowski, and E. Hovig, "A literature network of human genes for high-throughput analysis of gene expression," Nat. Genet., vol. 28, pp. 21-28, 2001.
21. B.J. Stapley and G. Benoit, "Biobibliometrics: Information retrieval and visualization from cooccurrences of gene names in Medline abstracts," Pac. Symp. Biocomput., pp. 529-540, 2000.
22. J.D. Wren and H.R. Garner, "Shared relationship analysis: Ranking set cohesion and commonalities within a literature-derived relationship network," Bioinformatics, vol. 20, pp. 191-198, 2004.
23. H. Shatkay, S. Edwards, W.J. Wilbur, and M. Boguski, "Genes, themes and microarrays: Using information retrieval for large-scale gene analysis," in Proc. Int. Conf Intell. Syst. Mol. Biol., vol. 8, pp. 317-328, 2000.
24. T.C. Rindflesch, L. Tanabe, J.N. Weinstein, and L. Hunter, "EDGAR: Extraction of drugs, genes and relations from the biomedical literature," Pac. Symp. Biocomput., pp. 517-528, 2000.
25. M. Ashburner, C.A. Ball, J.A. Blake, D. Botstein, H. Butler, J.M. Cherry, A.P. Davis, K. Dolinski, S.S. Dwight, J.T. Eppig, M.A. Harris, D.P. Hill, L. Issel-Tarver, A. Kasarskis, S. Lewis, J.C. Matese, J.E. Richardson, M. Ringwald, G.M. Rubin, and G. Sherlock, "Gene ontology: Tool for the unification of biology. The gene ontology consortium," Nat. Genet., vol. 25, pp. 25-29, 2000.
26. D.R. Swanson, "Undiscovered public knowledge," Library Q., no. 56, pp. 103-118, 1986.
27. D.R. Swanson, "Fish oil, Raynaud's syndrome, and undiscovered public knowledge," Perspect. Biol. Med., vol. 30, pp. 7-18, 1986.
28. D.R. Swanson, "Migraine and magnesium: Eleven neglected connections," Perspect. Biol. Med., vol. 31, pp. 526-557, 1988.
29. D.R. Swanson, "Somatomedin C and Arginine: Implicit connections between mutually isolated literatures," Perspect. Biol. Med., vol. 33, pp. 157-186, 1990.
30. D.R. Swanson and N.R. Smalheiser, "An interactive system for finding complementary literatures: A stimulus to scientific discovery," Artif. Intell., vol. 91, pp. 183-203, 1997.
31. D. Hristovski, J. Stare, B. Peterlin, and S. Dzeroski, "Supporting discovery in medicine by association rule mining in Medline and UMLS," Medinfo, vol. 10, pp. 1344-1348, 2001.
32. M. Weeber, H. Klein, A.R. Aronson, J.G. Mork, L.T. de Jong-van den Berg, and R. Vos, "Text-based discovery in biomedicine: The architecture of the DAD-system," Proc. AMIA Symp., pp. 903-907, 2000.
33. M. Weeber, R. Vos, H. Klein, L.T. De Jong-Van Den Berg, A.R. Aronson, and G. Molema, "Generating hypotheses by discovering implicit associations in the literature: A case report of a search for new potential therapeutic uses for thalidomide," J. Am. Med. Inform. Assoc., vol. 10, pp. 252-259, 2003.
34. R. Davis, H. Shrobe, and P. Szolovits, "What is a knowledge representation?," Al Mag., vol. 14, pp. 17-33, 1993.
35. D. Hume, An Enquiry Concerning Human Understanding. London: A. Millar, 1748.
36. K.R. Popper, Conjectures and Refutations: The Growth of Scientific Knowledge, 4th Ed. London, U.K.: Routledge & Kegan Paul, 1972.
37. V. Vinge,"The coming technological singularity: How to survive in the post-human era," presented at VISION-21 Symp., Westlake, Ohio, 1993.
38. B.J. Maclennan, "Flexible computing in the 21st century," Vector Register, vol. 4, pp. 8-12, 1991.