Mining the biomedical literature using semantic analysis and natural language processing techniques

Drug Discovery Today: BIOSILICO

Volumn 1, Issue 2, 2003, Pages 69-80

  Feldman, Ronen ^a   Regev, Yizhar ^b   Hurvitz, Eyal ^b   Finkelstein Landau, Michal ^b  

^a BAR ILAN UNIVERSITY   (Israel)

^b ClearForest Ltd   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

HELIX LOOP HELIX PROTEIN;

AGE; AUTOMATION; BIOMEDICINE; BIOPROCESS; COMPUTER LANGUAGE; ELECTRONICS; GENE INTERACTION; GENETIC IDENTIFICATION; HUMAN; INFORMATION RETRIEVAL; INTERNET; INTRANET; MACHINE; MEDICAL ASSESSMENT; MEDICAL DECISION MAKING; MEDICAL DOCUMENTATION; MEDICAL INFORMATION SYSTEM; MEDLINE; NONHUMAN; NUCLEOTIDE SEQUENCE; PHENOTYPE; PROBLEM SOLVING; PROTEIN MOTIF; REVIEW; SCIENCE; SEMANTICS;

EID: 15944417104     PISSN: 17418364     EISSN: None     Source Type: Journal    
DOI: 10.1016/s1478-5382(03)02330-8     Document Type: Review

References (51)

1. Ponte, J.M. and Croft, W.B. (1998) A language modeling approach to information retrieval. Proceedings of the 21st Annual International ACM SIGIR, 275-281
2. Salton, G. (1989) Automatic Text Processing: The Transformation, Analysis and Retrieval of Information by Computer, Addison-Wesley
3. Shatkay, H. et al. (2002) Information retrieval meets gene analysis. IEEE Intelligent Systems 17, 45-53
4. Allen, J. (1995) Natural Language Understanding, Addison-Wesley
5. Charniak, E. (1993) Statistical Language Learning, MIT Press
6. Frantzi, T.K. (1997) Incorporating context information for the extraction of terms. Presented at the conference of ACL-EACL, 7-11 July 1997, Madrid, Spain
7. Manning, C.D. and Schutze, H. (1999) Foundations of Statistical Natural Language Processing, MIT Press
8. Cardie, C. (1997) Empirical methods in information extraction. AI Magazine 18, 65-80
9. Chang, J.T. et al. (2001) Including biological literature improves homology search. Proceedings of the Pacific Symposium on Biocomputing 2001, 374-383
10. Cowie, J. and Lehnert, W. (1996) Information extraction. Comm. Assoc. Comput. Mach. 39, 80-91
11. Fisher, D. et al. (1995) Description of the UMass systems as used for MUC-6. Proceedings of the 6th Message Understanding Conference, 127-140
12. Grishman, R. (1996) The role of syntax in information extraction. In Advances in Text Processing: Tipster Program Phase II, Morgan Kaufmann
13. Lehnert, W. et al. (1993) Description of the CIRCUS system as used for MUC-3. Proceedings of the 3rd Message Understanding Conference, 223-223
14. Ray, S. and Craven, M. (2001) Representing sentence structure in hidden Markov models for information extraction. Presented at the International Joint Conference on Artificial Intelligence, August 4-10 2001, Seattle, WA, USA
15. Riloff, E. and Lehnert, W. (1994) Information extraction as a basis for high-precision text classification. ACM Transactions on Information Systems 12, 296-333
16. Akane, Y. et al. (2001) Event extraction from biomedical papers using a full parser. Proceedings of the Pacific Symposium on Biocomputing 2001, 408-419
17. Andrade, M.A. and Valencia, A. (1997) Automatic annotation for biological sequences by extraction of keywords from Medline abstracts. Development of a prototype system. Presented at the AAAI Conference of Intelligent Systems in Molecular Biology, June 21-26, Halkidiki, Greece
18. Blaschke, C. et al. (1999) Automatic extraction of biological information from scientific text: protein-protein interactions. Proceedings of the AAAI Conference on Intelligent Systems in Molecular Biology, 60-67
19. Craven , M. and Kumlien, J. (1999) Constructing biological knowledge bases by extracting information from text sources. Proceedings of the Intelligent Systems for Molecular Biology, 77-86
20. Ding, J. et al. (2002) Mining Medline: abstracts, sentences or phrases. Proceedings of the Pacific Symposium on Biocomputing, 326-337
21. Friedman, C. et al. (2001) GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Proceedings of the International Conference on Intelligent Systems for Molecular Biology, S74-S82
22. Fukuda, K. et al. (1998) Toward information extraction: identifying protein names from biological papers. Proceedings of the Pacific Symposium on Biocomputing 705-716
23. Humphreys, K. et al. (2000) Two applications of information extraction to biological science journal articles: interactions enzyme and protein structures. Proceedings of the Pacific Symposium on Biocomputing, 502-513
24. Krauthammer, M. et al. (2002) Truth of and pathways: chasing bits of information through myriads of articles. Proceedings of the International Conference on Intelligent Systems for Molecular Biology, S249-S257
25. Park, J. et al. (2001) Bidirectional incremental parsing for automatic pathway identification with combinatory categorical grammar. Proceedings of the Pacific Symposium on Biocomputing, 396-407
26. Pearson, H. (2001) Biology's name game. Nature 411, 631-632
27. Pustejovsky, J. et al. (2002) Robust relational parsing over biomedical literature: extracting inhibit relations. Proceedings of the Pacific Symposium on Biocomputing, 362-373
28. Rindflesch, T.C. et al. (2000) EDGAR: extraction of drugs, genes and relations from the biomedical literature. Proceedings of the Pacific Symposium on Biocomputing, 514-525
29. Spellman, P.T. (1998) Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridisation. Mol. Biol. Cell 9, 3273-3297
30. Stapley, B.J. and Benoit, G. (2000) BioBibliometrics: retrieval information and visualization from co-occurrences of gene names in Medline abstracts. Proceedings of the Pacific Symposium on Biocomputing, 526-537
31. Tanabe, L. et al. (1999) MedMiner: an internet text-mining tool for biomedical information, with application to gene expression profiling. BioTechniques 27, 1210-1217
32. Thomas, J. et al. (2002) Automatic extraction of protein interactions from scientific abstracts. Proceedings of the Pacific Symposium on Biocomputing, 538-549
33. Tor-Jenssen, K. et al. (2001) A literature network of human genes for high-throughput analysis of gene expression. Nat. Genet. 28, 21-28
34. Yeh, A. et al. (2003) Background and overview for KDD Cup 2002 Task 1: information extraction from biomedical articles. SIGKDD Explorations 4, 87-89
35. Feldman, R. and Hirsh, H. (1997) Exploiting background information in knowledge discovery from text. Journal of Intelligent Information Systems 9, 83-97
36. Feldman, R. et al. (1997) Maximal association rules: a new tool for mining for keyword co-occurrences in document collections. Presented at the 3rd International Conference on Knowledge Discovery, August 14-17 1997, Newport Beach, CA, USA
37. Frawley, W.J. et al. (1991) Knowledge discovery in databases: an overview. In Knowledge Discovery in Databases (Piatetsky-Shapiro, G. and Frawley, W.J., eds), pp. 1-27, MIT Press
38. Hayes, P. (1992) Intelligent high-volume processing using shallow, domain-specific techniques. In Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval, pp. 227-242, Lawrence Erlbaum, Hillside, New Jersey
39. Joachims, T. (1998) Text categorization with support vector machines: learning with many relevant features. Presented at the European Conference on Machine Learning, April 21-24 1998, Chemnitz, Germany
40. Sebastiani, F. (2002) Machine learning in automated text categorization . ACM Computing Surveys 34, 1-47
41. Hofmann, T. (1999) The cluster-abstraction model: unsupervised learning of topic hierarchies from text data. Proceedings of the Sixteenth Joint International Conference on Artificial Intelligence, 682-687
42. Aumann, Y. et al. ( 1999) Circle graphs: new visualization tools for text-mining. Proceedings of the 3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, 277-282
43. Hayes, P.J and Weinstein , S.P. (1990) CONSTRUE: a system for content-based indexing of a database of news stories. Presented at the Second Annual Conference on Innovative Applications of Artificial Intelligence, 1990, Washington DC, USA
44. Yang, Y. and Liu, X. (1999) A re-examination of text categorization methods. Proceedings of the ACM International Conference on Research and Development in Information Retrieval, 42-49
45. Feldman, R. et al. (2002) A comparative study of information extraction strategies. Proceedings of the Third International Conference on Intelligent Text Processing and Computational Linguistics, 349-359
46. Feldman, R. et al. (2001) A domain independent environment for creating information extraction modules. Proceedings of the Tenth International Conference on Information and Knowledge Management, 586-588
47. Feldman, R. et al. (2000) A framework for specifying explicit bias for revision of approximate information extraction rules. Proceedings of the Sixth ACM International Conference on Knowledge Discovery and Data Mining, 189-199
48. Cohen, K.B. et al. (2002) Contrast and variability in gene names. Proceedings of Natural Language Processing in the BioMedical Domain, 14-20
49. Lin, W.H. (1995) Expression of a Drosophila GATA transcription factor in multiple tissues in the developing embryos. Identification of homozygous lethal mutants with P-element insertion at the promoter region. J. Biol. Chem. 270, 25150-25158
50. Ghanem, M.M. et al. (2003) Automatic scientific text classification using local patterns: KDD CUP 2002 (Task 1). SIGKDD Explorations 4, 95-96
51. Regev, Y. et al. (2003) Rule-based extraction of experimental evidence in the biomedical domain - the KDD Cup (Task 1). SIGKDD Explorations 4, 90-92