Status of text-mining techniques applied to biomedical text

Drug Discovery Today

Volumn 11, Issue 7-8, 2006, Pages 315-325

  Erhardt, Ramón A A ^a   Schneider, Reinhard ^b   Blaschke, Christian ^a  

^a Bioalma   (Spain)

^b EUROPEAN MOLECULAR BIOLOGY LABORATORY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA BASE; DRUG RESEARCH; GRAMMAR; INFORMATION PROCESSING; INFORMATION RETRIEVAL; INFORMATION STORAGE; INFORMATION TECHNOLOGY; LINGUISTICS; MEDICAL DECISION MAKING; MEDICAL DOCUMENTATION; MEDICAL INFORMATICS; MEDICAL INFORMATION; MEDICAL INFORMATION SYSTEM; MEDICAL LITERATURE; MEDICAL RECORD; NOMENCLATURE; PHONETICS; PROCESS DEVELOPMENT; REVIEW; SEMANTICS; THEORETICAL STUDY;

ABSTRACTING AND INDEXING; ABSTRACTING AND INDEXING AS TOPIC; BIOMEDICAL RESEARCH; DATABASES, BIBLIOGRAPHIC; DICTIONARIES; DICTIONARIES AS TOPIC; HUMANS; INFORMATION STORAGE AND RETRIEVAL; LANGUAGE; NATURAL LANGUAGE PROCESSING; PATTERN RECOGNITION, AUTOMATED; PERIODICALS; PERIODICALS AS TOPIC; SEMANTICS; TERMINOLOGY; TERMINOLOGY AS TOPIC; VOCABULARY, CONTROLLED;

EID: 33645841072     PISSN: 13596446     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.drudis.2006.02.011     Document Type: Review

References (93)

1. Terry, W. (1971) Procedures as a representation for data in a computer program for understanding natural language. MIT AI Technical Report 235
2. Mallery, J.C.M. (1988) Thinking about foreign policy: finding an appropriate role for artificially intelligent computers The Annual Meeting of the International Studies Association St. Louis, MO, USA
3. Allen J. Natural Language Understanding. (2nd edn) (1995), Benjamin/Cummins Publishing
4. Russell S., and Norvig P. Artificial Intelligence: A Modern Approach (1995), Prentice Hall
5. In: Gorfein D.S. (Ed). On the Consequences of Meaning Selection: Perspectives on Resolving Lexical Ambiguity (2001), APA Books
6. Eric Brill and Philip Resnik. 1994. A rule-based approach to prepositional phrase attachment disambiguation. In Proceedings of the 15th conference on Computational Linguistics, 1198-1204
7. Pantel, P. and Lin, D. 2000. An unsupervised approach to prepositional phrase attachment using contextually similar words. In Proc. of ACL-2000, Hong Kong
8. Dagan I., et al. Contextual word similarity and estimation from sparse data. Computer, Speech and Language 9 (1995) 123-152
9. Li, H. and Abe, N. (1998) Word clustering and disambiguation based on co-occurrence data. In Proceedings of COLING
10. Lin D. Automatic retrieval and clustering of similar words. Proceedings of the 36th Annual Meeting of the Association for Computational Linguistic 2 (1998) 768-774
11. Fellbaum C. WordNet: an Electronic Lexical Database (1999), MIT Press
12. Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 32 Database issue (2004) D267-D270
13. Bada M., et al. A short study on the success of the Gene Ontology. J. Web Semantics 1 (2004) 235-240
14. Ginter F., et al. New Techniques for Disambiguation in Natural Language and Their Application to Biological Text. J. Mach. Learn. Res. 5 (2004) 605-621
15. Jurafsky D., and Martin J.H. Speech and language processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2000), Prentice-Hall
16. Appelt, D.E. and Israel, D.J. (1999) Introduction to information extraction technology. In Proceedings of the 16th International joint Conference on Artificial Intelligence, Stockholm, Sweden
17. Jensen LJ, Saric J, Bork P. (2003) Utilizing literature for biological discovery. E-BioSci/ORIEL Annual Workshop. Varenna, Italy
18. Jenssen T.K., et al. A literature network of human genes for high-throughput analysis of gene expression. Nat. Genet. 28 (2001) 21-28
19. Fukuda K. et al. (1998) Toward Information Extraction: Indentifying Protein Names from Biological Papers. In Proceedings of the Pacific Symposium on Biocomputing. 3, 707-718.
20. Proux D., et al. Detecting Gene Symbols and Names in Biological Texts: A First Step toward Pertinent Information Extraction. Genome Inform. Ser. Workshop Genome Inform. 9 (1998) 72-80
21. Rindflesch T.C., et al. EDGAR: extraction of drugs, genes and relations from the biomedical literature. Pac. Symp. Biocomput. 5 (2000) 517-528
22. Tanabe L., and Wilbur W.J. Tagging gene and protein names in biomedical text. Bioinformatics 18 (2002) 1124-1132
23. Wilbur W.J., et al. Analysis of biomedical text for chemical names: a comparison of three methods. Proc. AMIA Symp. (1999) 176-180
24. Adamic A.L., et al. A Literature Based Method for Identifying Gene-Disease Connections. Proceedings of the IEEE Comput. Soc. Bioinform. Conf. 1 (2002) 109-117
25. Grishman R., et al. Information extraction for enhanced access to disease outbreak reports. J. Biomed. Inform. 35 (2002) 236-246
26. Friedman C., et al. Automated encoding of clinical documents based on natural language processing. J. Am. Med. Inform. Assoc. 11 (2004) 392-402
27. Wren J.D., and Garner H.R. Shared relationship analysis: ranking set cohesion and commonalities within a literature-derived relationship network. Bioinformatics 20 (2004) 191-198
28. Torii M., et al. Using name-internal and contextual features to classify biological terms. J. Biomed. Inform. 37 (2004) 498-511
29. Zhou G., et al. Recognizing names in biomedical texts: a machine learning approach. Bioinformatics 20 (2004) 1178-1190
30. Lee K.J., et al. Biomedical named entity recognition using two-phase model based on SVMs. J. Biomed. Inform. 37 (2004) 436-447
31. Kim J.D., et al. GENIA corpus-semantically annotated corpus for bio-textmining. Bioinformatics 19 Suppl 1 (2003) i180-i182
32. Mons B. Which gene did you mean?. BMC Bioinformatics 6 (2005) 142
33. Chen L., et al. Gene name ambiguity of eukaryotic nomenclatures. Bioinformatics 21 (2004) 248-256
34. Tuason O., et al. Biological nomenclatures: a source of lexical knowledge and ambiguity. Pac. Symp. Biocomput. 8 (2004) 238-249
35. Schuemie M.J., et al. Word sense disambiguation in the biomedical domain: an overview. J. Comput. Biol. 12 (2005) 554-565
36. Leroy G., and Rindflesch T.C. Effects of information and machine learning algorithms on word sense disambiguation with small datasets. Int. J. Med. Inform. 74 (2005) 573-585
37. Liu H., et al. Disambiguating ambiguous biomedical terms in biomedical narrative text: an unsupervised method. J. Biomed. Inform. 34 (2001) 249-261
38. Cohen, A. (2005) Unsupervised gene/protein named entity normalization using automatically extracted dictionaries. Proceedings of the Joint ACL Workshop and BioLINK SIG (ISMB) on Linking Biological Literature Ontologies and Databases Detroit, MI, USA
39. Schijvenaars B.J., et al. Thesaurus-based disambiguation of gene symbols. BMC Bioinformatics 6 (2005) 149
40. Morgan A.A., et al. Gene name identification and normalization using a model organism database. J. Biomed. Inform. 37 (2004) 396-410
41. Podowski, R.M. et al. (2004) AZuRE, a Scalable System for Automated Term Disambiguation of Gene and Protein Names. In 3rd International IEEE Computer Society Computational Systems Bioinformatics Conference. IEEE Computer Society, 415-424
42. Tanabe, L. and Wilbur, W.J. (2002) Tagging gene and protein names in full text articles. Proceedings of the ACL Workshop on Natural Language Processing in the Biomedical Domain. 9-13
43. Liu H., et al. A study of abbreviations in MEDLINE abstracts. Proc. AMIA Symp. (2002) 464-468
44. Wren D.J., et al. Biomedical Term Mapping Databases. Nucleic Acids Research (Database Issue) 33 (2005) 289-293
45. Chang J.T., et al. Creating an online dictionary of abbreviations from MEDLINE. J. Am. Med. Inform. Assoc. 9 (2002) 612-620
46. Yu H., et al. Mapping abbreviations to full forms in biomedical articles. J. Am. Med. Inform. Assoc. 9 (2002) 262-272
47. Pustejovsky J., et al. Automatic extraction of acronym-meaning pairs from MEDLINE databases. Medinfo 10 (2001) 371-375
48. Podowski R.M., et al. Suregene, a scalable system for automated term disambiguation of gene and protein names. J Bioinform Comput Biol. 3 (2005) 743-770
49. Hirschman L., et al. Overview of BioCreAtIvE task 1B: normalized gene lists. BMC Bioinformatics 6 Suppl 1 (2005) S11
50. Hirschman L., et al. Overview of BioCreAtIvE: critical assessment of information extraction for biology. BMC Bioinformatics 6 Suppl 1 (2005) S1
51. Yeh A., et al. BioCreAtIvE Task 1A: gene mention finding evaluation. BMC Bioinformatics 6 Suppl 1 (2005) S2
52. Kinoshita S., et al. BioCreAtIvE Task1A: entity identification with a stochastic tagger. BMC Bioinformatics 6 Suppl. 1 (2005) S4
53. Finkel J., et al. Exploring the boundaries: gene and protein identification in biomedical text. BMC Bioinformatics 6 Suppl. 1 (2005) S5
54. Hakenberg J., et al. Systematic feature evaluation for gene name recognition. BMC Bioinformatics 6 Suppl. 1 (2005) S9
55. Crim J., et al. Automatically annotating documents with normalized gene lists. BMC Bioinformatics 6 Suppl. 1 (2005) S13
56. Hanisch D., et al. ProMiner: rule-based protein and gene entity recognition. BMC Bioinformatics 6 Suppl. 1 (2005) S14
57. Fundel K., et al. A simple approach for protein name identification: prospects and limits. BMC Bioinformatics 6 Suppl. 1 (2005) S15
58. Tamames J. Text Detective: a rule-based system for gene annotation in biomedical texts. BMC Bioinformatics 6 Suppl. 1 (2005) S10
59. Hersh W., et al. Enhancing access to the bibliome: the TREC genomics track. Medinfo 11 (2004) 773-777
60. Blaschke C., et al. Automatic extraction of biological information from scientific text: protein-protein interactions. Proc Int Conf Intell Syst Mol Biol. 30A (1999) 60-67
61. Ng S., and Wong M. Toward routine automatic pathway discovery from on-line scientific text abstracts. Genome Informatics 10 (1999) 104-112
62. Wong L. PIES, a protein interaction extraction system. Pac. Symp. Biocomput. 6 (2001) 520-531
63. Daraselia N., et al. Extracting human protein interactions from MEDLINE using a fullsentence parser. Bioinformatics 22 (2004) 604-611
64. Friedman C., et al. GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformaticas 17 Suppl. 1 (2001) S74-S82
65. Rindflesch T.C., et al. Mining molecular binding terminology from biomedical text. Proc. AMIA Symp. 34 (1999) 127-131
66. Saric J., et al. Extraction of regulatory gene/protein networks from Medline. Bioinformatics July (2005) 26
67. Thomas J., et al. Automatic extraction of protein interactions from scientific abstracts. Pac. Symp. Biocomput. (2000) 541-552
68. Wattarujeekrit T., et al. PASBiol.: predicate-argument structures for event extraction in molecular biology. BMC Bioinformatics 5 (2004) 155
69. Chiang J.H., et al. GIS: a biomedical text-mining system for gene information discovery. Bioinformatics 20 (2004) 120-121
70. Adamic L.A., et al. A literature based method for identifying gene-disease connections. Proc. IEEE Comput. Soc. Bioinform. Conf. 1 (2002) 109-117
71. Divoli A., and Attwood T.K. BioIE: extracting informative sentences from the biomedical literature. Bioinformatics 21 (2005) 2138-2139
72. Koike A., et al. Automatic extraction of gene/protein biological functions from biomedical text. Bioinformatics 21 (2004) 1227-1236
73. Hahn U., et al. MEDSYNDIKATE-a natural language system for the extraction of medical information from findings reports. Int. J. Med. Inform. 67 (2002) 63-74
74. do Amaral M.B., et al. NLP techniques associated with the OpenGALEN ontology for semi-automatic textual extraction of medical knowledge: abstracting and mapping equivalent linguistic and logical constructs. Proc. AMIA Symp. (2000) 76-80
75. Friedman C., et al. Representing information in patient reports using natural language processing and the extensible markup language. J. Am. Med. Inform. Assoc. 6 (1999) 76-87
76. Libbus B., and Rindflesch T.C. NLP-based information extraction for managing the molecular biology literature. Proc. AMIA Symp. (2002) 445-449
77. Donaldson I., et al. PreBIND and Textomy-mining the biomedical literature for protein-protein interactions using a support vector machine. BMC Bioinformatics 4 (2003) 11
78. Nédellec, C. (2005) Learning language in logic - genic interaction extraction challenge, (Cussens, J. and Nédellec, C., eds) In Proceedings of the 4th Learning Language in Logic Workshop (LLL05) 31-37, Bonn, Germany
79. Stapley B.J., and Benoit G. Biobibliometrics: information retrieval and visualization from co-occurrences of gene names in Medline abstracts. Pac. Symp. Biocomput. 5 (2000) 529-540
80. Andrade M.A., and Valencia A. Automatic extraction of keywords from scientific text: application to the knowledge domain of protein families. Bioinformatics 14 (1998) 600-607
81. Shatkay H., et al. Genes, themes, and microarrays: using information retrieval for largescale gene analysis. Intell. Syst. Mol. Biol. 8 (2000) 317-328
82. Blaschke C., et al. Mining functional information associated with expression arrays. Funct. Integr. Genomics 1 (2001) 256-268
83. Raychaudhuri S., et al. The computational analysis of scientific literature to define and recognize gene expression clusters. Nucleic Acids Res. 31 (2003) 4553-4560
84. Rubinstein R., and Simon I. MILANO-custom annotation of microarray results using automatic literature searches. BMC Bioinformatics 6 (2005) 12
85. Blaschke C., and Valencia A. Automatic ontology construction from the literature. Genome Informatics 13 (2002) 201-213
86. Homayouni R., et al. Gene clustering by latent semantic indexing of MEDLINE abstracts. Bioinformatics 21 (2005) 104-115
87. Raychaudhuri S., et al. Using text analysis to identify functionally coherent gene groups. Genome Res. 12 (2002) 1582-1590
88. Tamames J., et al. EUCLID: automatic classification of proteins in functional classes by their database annotations. Bioinformatics 14 (1998) 542-543
89. Perez A.J., et al. Gene annotation from scientific literature using mappings between keyword systems. Bioinformatics 20 (2004) 2084-2091
90. Raychaudhuri S., et al. Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature. Genome Res. 12 (2002) 203-214
91. Chang J.T., et al. Including biological literature improves homology search. Pac. Symp. Biocomput. 6 (2001) 374-383
92. Perez-Iratxeta C., et al. Association of genes to genetically inherited diseases using data mining. Nat. Genet. 31 (2002) 316-319
93. de Bruijn B., and Martin J. Getting to the (c)ore of knowledge: mining biomedical literature. Int. J. Med. Inform. 67 (2002) 7-18