Knowledge Management for Biomedical Literature: The Function of Text-Mining Technologies in Life-Science Research

UNSPECIFIED Knowledge Management for Biomedical Literature: The Function of Text-Mining Technologies in Life-Science Research., 2008 [Conference proceedings]

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English abstract

Efficient information retrieval and extraction is a major challenge in life-science research. The Knowledge Management (KM) for biomedical literature aims to establish an environment, utilizing information technologies, to facilitate better acquisition, generation, codification, and transfer of knowledge. Knowledge Discovery in Text (KDT) is one of the goals in KM, so as to find hidden information in the literature by exploring the internal structure of knowledge network created by the textual information. Knowledge discovery could be major help in the discovery of indirect relationships, which might imply new scientific discoveries. Text-mining provides methods and technologies to retrieve and extract information contained in free-text automatically. Moreover, it enables analysis of large collections of unstructured documents for the purposes of extracting interesting and non-trivial patterns of knowledge. Biomedical text-mining is organized in stages classified into the following steps: identification of biological entities, identification of biological relations and classification of entity relations. Here, we discuss the challenges and function of biomedical text-mining in the KM for biomedical literature.

Item type: Conference proceedings
Keywords: Knowledge Management (KM);Biomedical Tex-Mining; Natural Language Processing (NLP)
Subjects: L. Information technology and library technology > LL. Automated language processing.
Depositing user: Carmen Galvez
Date deposited: 30 Mar 2008
Last modified: 02 Oct 2014 12:11
URI: http://hdl.handle.net/10760/11339

References

[1] Koehler J. Editorial. Briefings in Bioinformatics 2005; 6 (3): 220–221.

[2] Humphreys BL, Lindberg DA, Schoolman HM, Barnett GO. The Unified Medical Language System: informatics research collaboration. J Am Med Inform Assoc 1998; 5(1): 1–11.

[3] Gene Ontology Consortium. Gene Ontology: tool for the unification of biology. Nat Genet 2000; 25(1):25-9.

[4] Leroy G, Chen H. Genescene: an ontology-enhanced integration of linguistic and co-occurrence based relations in biomedical texts. J Am Soc Inf Sci Technol 2005; 56 (5): 457–68.

[5] Hersh W. Evaluation of biomedical text-mining systems: lessons learned from information retrieval. Briefings in Bioinformatics 2005; 6 (4): 344–56.

[6] Ananiadou S. Challenges of term extraction in biomedical texts. Available at: http://www.pdg.cnb.uam.es/BioLink/workshop_BioCreative_04/handout/

[7] Morgan AA, Hirschman L, Colosimo M, Yeh AS, Colombe JB. Gene name identification and normalization using a model organism database. J Biomed Informat 2004; 37: 396–410.

[8] Tuason O, Chen L, Liu H, Blake J, Friedman C. Biological nomenclatures: a source of lexical knowledge and ambiguity. In: Pac Symp Biocomput 2004. p. 238–49.

[9] Stapley BJ, Benoit G. Biobibliometrics: information retrieval and visualization from co-occurrence of gene names in Medline abstracts. In: Pac Symp Biocomput; 2000. p. 529–40.

[10] 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(1): 21–8.

[11] Stephens M, Palakal M, Mukhopadhyay S, Raje R, Mostafa J. Detecting gene relations from MEDLINE abstracts. In: Pac Symp Biocomput 2001:483–496.

[12] Iliopoulos I, Enright AJ, Ouzounis CA. Textquest: document clustering of MEDLINE abstracts for concept discovery in molecular biology. In: Pac Symp Biocomput; 2001. p. 384–395.

[13] Pearson H. Biology's name game. Nature 2001;411:631–2.

[14] Hirschman L, Park C, Tsujii J, Wong L, Wu CH. Accomplishments and challenges in literature data mining for biology. Bioinformatics 2002; 18(12): 1553–61.


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