A concept-driven biomedical knowledge extraction and visualization framework for conceptualization of text corpora

Journal of Biomedical Informatics

Volumn 43, Issue 6, 2010, Pages 1020-1035

  Jahiruddin, ^a   Abulaish, Muhammad ^a   Dey, Lipika ^b  

^a JAMIA MILLIA ISLAMIA CENTRAL UNIVERSITY   (India)

^b TATA CONSULTANCY SERVICES   (India)

Author keywords

Biological relation extraction; Biological text mining; Biomedical knowledge extraction and visualization; Biomedical query answering; Semantic network

Indexed keywords

KNOWLEDGE EXTRACTION; QUERY ANSWERING; RELATION EXTRACTION; SEMANTIC NETWORK; TEXT MINING;

CHARACTER RECOGNITION; CLASSIFICATION (OF INFORMATION); COMPUTATIONAL LINGUISTICS; DATA MINING; INFORMATION SYSTEMS; NATURAL LANGUAGE PROCESSING SYSTEMS; PATTERN MATCHING; SEARCH ENGINES; TEXT PROCESSING; VISUALIZATION;

INFORMATION RETRIEVAL SYSTEMS;

ARTICLE; BIOMEDICINE; CLASSIFICATION; CONCEPTUAL FRAMEWORK; DATA MINING; GENETIC TRANSCRIPTION; HUMAN; INFORMATION PROCESSING; KNOWLEDGE; LANGUAGE PROCESSING; LINGUISTICS; NATURAL LANGUAGE PROCESSING; PRIORITY JOURNAL;

ABSTRACTING AND INDEXING AS TOPIC; ALGORITHMS; INFORMATION STORAGE AND RETRIEVAL; NATURAL LANGUAGE PROCESSING; SEMANTICS;

EID: 78649323301     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2010.09.008     Document Type: Article

References (34)

1. Uramoto N., Matsuzawa H., Nagano T., Murakami A., Takeuchi H., Takeda K. A text-mining system for knowledge discovery from biomedical documents. IBM Syst J 2004, 43(3):516-533.
2. Muller H.M., Kenny E.E., Strenber P.W. Textpresso: an ontology-based information retrieval and extraction system for biological literature. PloS Biol 2004, 2(11):e309. http://www.plosbiology.org.
3. Shatkay H., et al. Information retrieval meets gene analysis. IEEE Intell Syst 2002, 17:45-53.
4. Allen J. Natural language understanding 2004, Pearson Education (Singapore) Pvt. Ltd., Indian branch. 2nd ed.
5. Schuler G.D., et al. Entrez: molecular biology database and retrieval system. Methods Enzymol 1996, 266:141-162.
6. Cowie J., Lehnert W. Information extraction. Comm Assoc Comput Mach 1996, 39:80-91.
7. Riloff E., Lehnert W. Information extraction as a basis for high-precision text classification. ACM Trans Inform Syst 1994, 12:296-333.
8. Ding J, et al. Mining medline: abstracts, sentences or phrases. In: Proceedings of the pacific symposium on biocomputing, 2002. p. 326-37.
9. Sekimizu T., Park H.S., Tsujii J. Identifying the interaction between genes and genes products based on frequently seen verbs in Medline abstract. Genome Inform 1998, 9:62-71.
10. Thomas J, Milward D, Ouzounis C, Pulman S, Carroll M. Automatic extraction of protein interactions from scientific abstracts. In: Pacific symposium on biocomputing, 2000. p. 538-49.
11. Ono T., Hishigaki H., Tanigami A., Takagi T. Automated extraction of information on protein-protein interactions from the biological literature. Bioinformatics 2001, 17(2):155-161.
12. Rinaldi F, Scheider G, Andronis C, Persidis A, Konstani O. Mining relations in the GENIA corpus. In: Proceedings of the 2nd European workshop on data mining and text mining for bioinformatics, Pisa, Italy, 2004.
13. Settles B. ABNER: an open source tool for automatically tagging genes, proteins, and other entity names in text. Bioinformatics 2005, 21(14):3191-3192.
14. Schutz A, Buitelaar P. RelExt: a tool for relation extraction from text in ontology extension. In: International semantic web conference, 2005. p. 593-606.
15. Yakushiji A, Teteisi Y, Miyao Y, Tsujii J. Event extraction from biomedical papers using a full parser. In: Pac Symp Biocomput, 2001. p. 408-409.
16. Cox E. A hybrid technology approach to free-form text data mining. Scianta Intelligence, 2005. URL: http://scianta.com/pubs/AR-PA-007.htm.
17. Castro A.G., et al. The use of concept maps during knowledge elicitation in ontology development processes - the nutrigenomics use case. BMC Bioinform 2006, 7(267).
18. Ciaramita M, Gangemi A, Ratsch E, Saric J, Rojas I. Unsupervised learning of semantic relations between concepts of a molecular biology ontology. In: Proceedings of the 19th international joint conference on artificial intelligence (IJCAI'05), 2005. p. 659-64.
19. Feldman R, et al. Maximal association rules: a new tool for mining for keyword co-occurrences in document collections. In: Proceedings of the 3rd international conference on knowledge discovery, Newport Beach, CA, USA, 1997. p. 167-70.
20. Aumann Y, et al. Circle graphs: new visualization tools for textmining. In: Proceedings of the 3rd European conference on principles and practice of knowledge discovery in databases, 1999. p. 277-82.
21. Jenssen T.-K., Laegreid A., Komorowski J., Hovig E. A literature network of human genes for high-throughput analysis of gene expression. Nat Genet 2001, 28:21-28.
22. Gaizauskas R., Demetriou G., Artymiuk P.J., Willett P. Protein structures and information extraction from biological texts: the PASTA system. Bioinformatics 2003, 19(1):135-143.
23. Friedman C., Kra P., Yu H., Krauthammer M., Rzhetsky A. GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics 2001, 17(1):s74-s82.
24. Zheng H.-T., Borchert C., Kim H.-G. Exploiting gene ontology to conceptualize biomedical document collections. LNCS 2008, vol. 5367. Springer, Berlin/Heidelberg, p. 375-89.
25. Plaisant C., Fekete J.-D., Grinsteinn G. Promoting insight-based evaluation of visualizations: from contest to benchmark repository. IEEE Trans Visual Comput Graph 2008, 14(1):120-134.
26. Landauer T., Foltz P., Laham D. Introduction to latent semantic analysis. Discourse Process 1998, 25:259-284.
27. Zheng H-T, Borchert C, Kim H-G. A concept-driven automatic ontology generation approach for conceptualization of document corpora. In: Proceedings of the 2008 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology, vol. 01, 2008. p. 352-58.
28. Kim J.-D., Ohta T., Tateisi Y., Tsujii J. GENIA corpus - a semantically annotated corpus for bio-textmining. Bioinformatics 2003, 19(1):i180-i182.
29. Salton G., McGill M.J. Introduction to modern information retrieval 1986, McGraw-Hill, Inc., New York, USA, ISBN:0070544840.
30. Porter M.F. An algorithm for suffix stripping. Program 1980, 14(3):130-137.
31. Berry MW, Hendrickson B, Raghavan P. Sparse matrix reordering schemes for browsing hypertext. In: Renegar J, Shub M, Smale S, editors. Lecture in applied mathematics, vol. 32, 1996. p. 99-123.
32. Abulaish M., Dey L. Biological relation extraction and query answering from medline abstracts using ontology-based text mining. Data Knowl Eng 2007, 61(2):228-262.
33. Fundel K., Kuffner R., Zimmer R. RelEx - relation extraction using dependency parse trees. Bioinformatics 2007, 23:365-371.
34. Li J., Zhang Z., Li X., Chen H. Kernel-based learning for biomedical relation extraction. J Am Soc Inform Sci Technol 2008, 59(5):756-769.