생의학 문헌에서 질병 관련 정보를 추출하기 위한 텍스트 마이닝 기법

  • Published : 2015.04.16

Abstract

Keywords

Acknowledgement

Supported by : 한국연구재단

References

  1. ZHOU, Guodong, et al. Recognizing names in biomedical texts: a machine learning approach. Bioinformatics, 2004,20.7: 1178-1190. https://doi.org/10.1093/bioinformatics/bth060
  2. MOLLA, Diego; VAN ZAANEN, Menno; SMITH, Daniel. Named entity recognition for question answering. Proceedings of ALTW, 2006, 51-58.
  3. KNOPP, Johannes; FRANK, Anette; RIEZLER, Stefan. Classification of named entities in a large multilingual resource using the Wikipedia category system. 2010. PhD Thesis. Master's thesis, University of Heidelberg.
  4. DOGAN, Rezarta Islmnaj; LEAMAN, Robert; LU, Zhiyong. NCBI disease corpus: a resource for disease name recognition and concept normalization. Journal of biomedical informatics, 2014, 47: 1-10. https://doi.org/10.1016/j.jbi.2013.12.006
  5. LEAMAN, Robert, et al. BANNER: an executable survey of advances in biomedical named entity recognition. In: Pacific Symposium on Biocomputing. 2008. p. 652-663.
  6. SETTLES, Bun. ABNER: an open source tool for automatically tagging genes, proteins and other entity names in text. Bioinformatics, 2005, 21.14:3191-3192. https://doi.org/10.1093/bioinformatics/bti475
  7. CARPENTER, Bob. LingPipe for 99.99% recall of gene mentions. In: Proceedings of the Second BioCreative Challenge Evaluation Workshop. 2007. p. 307-309
  8. BALDWIN, Breck; CARPENTER, Bob. LingPipe. Available from World Wide Web: http://alias-i.com/lingpipe, 2003.
  9. ARONSON, Alan R. Metamap: Mapping text to the umls metathesaurus. Bethesda, MD:NLM, NIH, DHHS, 2006, 1-26.
  10. ARONSON, Alan R. ; LANG, Francois-Michel. An overview of MetaMap: historical perspective and recent advances. Journal of the American Medical Informatics Association, 2010, 17.3: 229-236. https://doi.org/10.1136/jamia.2009.002733
  11. LEAMAN, Robert; DOGAN, Rezarta Islamaj; LU, Zhiyong. DNorm: disease name normalization with pairwise learning to rank. Bioinformatics, 2013, btt474.
  12. ALAKO, Blaise TF, et al. CoPub Mapper: mining MEDLINE based on search term co-publication. BMC bioinformatics, 2005, 6.1: 51. https://doi.org/10.1186/1471-2105-6-51
  13. KIM, Jin Dong, et al. EXTRACTING BIO MOLECULAR EVENTS FROM LITERATURE-THE BIONLP'09 SHARED TASK. Computational Intelligence, 2011, 27.4: 513-540. https://doi.org/10.1111/j.1467-8640.2011.00398.x
  14. KIM, Jin-Dong, et al. Overview of BioNLP shared task 2011 . In: Proceedings of the BioNLP Shared Task 2011 Workshop. Association for Computational Linguistics, 2011. p. 1-6.
  15. NEDELLEC, Claire, et al. Overview of BioNLP shared task 2013. In:Proceedings of the BioNLP Shared Task 2013 Workshop. 2013. p. 1-7.
  16. BUI, Quoc-Chinh, et al. A fast rule-based approach for biomedical event extraction. In: Proceedings of the BioNLP Shared Task 2013 Workshop. 2013. p.104-108.
  17. BJORNE, Jari; SALAKOSKI, Tapio. TEES 2.1: Automated annotation scheme learning in the BioNLP 2013 shared task. In: Proceedings of the BioNLP Shared Task 2013 Workshop. 2013. p. 16-25.
  18. RIEDEL, Sebastian; MCCALLUM, Andrew. Robust biomedical event extraction with dual decomposition and minimal domain adaptation. In: Proceedings of the BioNLP Shared Task 2011 Workshop. Association for Computational Linguistics, 2011. p. 46-50.
  19. RATKOVIC, Zorana; GOLIK, Wiktoria; WARNIER, Pierre. Event extraction of bacteria biotopes: a knowledge-intensive NLP-based approach. BMC bioinformatics, 2012, 13.Suppl 11: S8.
  20. MCCLOSKY, David, et al. Combining joint models for biomedical event extraction. BMC bioinformatics, 2012, 13.Suppl 11: S9.
  21. MIWA, Makoto, et al. Event extraction with complex event classification using rich features. Journal of bioinformatics and computational biology, 2010, 8.01: 131-146. https://doi.org/10.1142/S0219720010004586
  22. HOFFMANN, Robert; VALENCIA, Alfonso. Implementing the iHOP concept for navigation of biomedical literature. Bioinformatics, 2005, 21.suppI 2: ii252-ii258.
  23. TSURUOKA, Yoshimasa, et al. Discovering and visualizing indirect associations between biomedical concepts. Bioinformatics, 2011, 27.13: i111-i119. https://doi.org/10.1093/bioinformatics/btr214
  24. POON, Hoifung, et al. Literome: PubMed-scale genomic knowledge base in the cloud. Bioinformatics, 2014, 30.19: 2840-2842. https://doi.org/10.1093/bioinformatics/btu383
  25. KIM, Jeongkyun, et al. DigSee: disease gene search engine with evidence sentences (version cancer). Nucleic acids research, 2013, gkt531.
  26. LEE, Hee-Jin, et al. OncoSearch: cancer gene search engine with literature evidence. Nucleic acids research, 2014, gku368.
  27. VANHECKE, Thomas E., et al. PubMed vs. HighWire Press: A head-to-head comparison of two medical literature search engines. Computers in biology and medicine, 2007, 37.9: 1252-1258. https://doi.org/10.1016/j.compbiomed.2006.11.012
  28. DAVIS, Allan Peter, et al. MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database. Database, 2012, 2012: bar065.