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Analyzing LBD Methods using a General Framework

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Part of the book series: Information Science and Knowledge Management ((ISKM,volume 15))

Abstract

This chapter provides a birds-eye view of the methods used for literature-based discovery (LBD). We study these methods with the help of a simple framework that emphasizes objects, links, inference methods, and additional knowledge sources. We consider methods from a domain independent perspective. Specifically, we review LBD research on postulating gene —disease connections, LBD systems designed for general purpose biomedical discovery goals, as well as LBD research applied to the web. Opportunities for new methods, gaps in our knowledge, and critical differences between methods are recognized when the “literature on LBD” is viewed through the scope of our framework. The main contributions of this chapter are in presenting open problems in LBD and outlining avenues for further research.

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References

  1. Lada A. Adamic and Eytan Adar. Friends and neighbors on the web. Social Networks, 25(3):211–230, 2003

    Article  Google Scholar 

  2. Lada A. Adamic, Dennis Wilkinson, Bernardo A. Huberman, and Eytan Adar. A Literature Based Method for Identifying Gene-Disease Connections. In Proceedings of the IEEE Computer Society Bioinformatics Conference (CSB 2002), pp. 109–117, 2002

    Google Scholar 

  3. Rakesh Agrawal and Ramakrishnan Srikant. Mining Sequential Patterns. In Proceedings of the Eleventh International Conference on Data Engineering, pp. 3–14, 1995

    Google Scholar 

  4. Michael Ashburner, Catherine A. Ball, Judith A. Blake, David Botstein, Heather Butler, J Micheal Cherry, Allan P. Davis, Kara Dolinski, Selina S. Dwight, Janan T. Eppig, Midori A. Harris, David P. Hill, Laurie Issel-Tarver, Andrew Kasarskis, Suzanna Lewis, John C. Matese, Joel E. Richardson, Martin Ringwald, Gerald M. Rubin, and Gavin Sherlock. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genetics, 25:2529, 2000

    Google Scholar 

  5. Moty Ben-Dov, Wendy Wu, Ronan Feldman, and Paul A. Cairns. Improving Knowledge Discovery by Combining Text-Mining and Link-Analysis Techniques. In Proceedings of the SIAM International Conference on Data Mining, 2004

    Google Scholar 

  6. Abraham Bernstein, Scott Clearwater, Shawndra Hill, Claudia Perlich, and Foster Provost. Discovering Knowledge from Relational Data Extracted from Business News. In Proceedings of Workshop on Multi-Relational Data Mining (MRDM 2002), 2002

    Google Scholar 

  7. Peter M. Bowers, Matteo Pellegrini, Mike J. Thompson, Joe Fierro, Todd O. Yeates, and David Eisenberg. Prolinks: a database of protein functional linkages derived from coevolution. Genome Biology, 5(R35), 2004

    Google Scholar 

  8. Hao Chen and Burt M. Sharp. Content-rich biological network constructed by mining PubMed abstracts. BMC Bioinformatics, 5(147), 2004

    Google Scholar 

  9. Kenneth A. Cory. Discovering hidden analogies in an online humanities database. Computers and the Humanities, 31:1–12, 1997

    Article  Google Scholar 

  10. Michael D. Gordon, Robert K. Lindsay, and Weiguo Fan. Literature-based discovery on the World Wide Web. ACM Transactions on Internet Technologies (TOIT), 2(4):261–275, 2002

    Article  Google Scholar 

  11. Ramanathan V. Guha and A. Garg. Disambiguating People in Search. Technical Report, Stanford University, 2004

    Google Scholar 

  12. Peter R. Holt, Seymour Katz, and Robert Kirshoff. Curcumin therapy in inflammatory bowel disease: a pilot study. Digestive Diseases and Sciences, 50(11):2191–2193, 2005

    Article  Google Scholar 

  13. Dimitar Hristovski, Borut Peterlin, Joyce A. Mitchell, and Susanne M. Humphrey. Improving literature based discovery support by genetic knowledge integration. Studies in Health Technology and Informatics, 95:68–73, 2003

    Google Scholar 

  14. Dimitar Hristovski, Janez Stare, Borut Peterlin, and Saso Dzeroski. Supporting discovery in medicine by association rule mining in medline and UMLS. Medinfo, 10(Pt 2):1344–1348, 2001

    Google Scholar 

  15. Yanhui Hu, Lisa M. Hines, Haifeng Weng, Dongmei Zuo, Miguel Rivera, Andrea Richardson, and Joshua LaBaer. Analysis of genomic and proteomic data using advanced literature mining. Journal of Proteome Research, 2:405–12, 2003

    Article  Google Scholar 

  16. Thomas Karopka, Juliane Fluck, Heinz-Theodor Mevissen, and Änne Glass. The Autoimmune Disease Database: a dynamically compiled literature-derived database. BMC Bioinformatics, 7(325), 2006

    Google Scholar 

  17. Ravi Kumar, Prabhakar Raghavan, Sridhar Rajagopalan, and Andrew Tomkins. Trawling the Web for Emerging Cyber-Communities. In Proceedings of the Eighth International Conference on World Wide Web (WWW-8), pp. 1481–1493, 1999

    Google Scholar 

  18. Holger Maier, Stefanie Döhr, Korbinian Grote, Sean O’Keeffe, Thomas, Werner, Martin Hrabé de Angelis, and Ralf Schneider. LitMiner and WikiGene: identifying problem-related key players of gene regulation using publication abstracts. Nucleic Acids Research, 33:W779–W782, 2005

    Article  Google Scholar 

  19. Hong Pan, Li Zuo, Vidhu Choudhary, Zhuo Zhang, Shoi H. Leow, Fui T. Chong, Yingliang Huang, Victor W.S. Ong, Bijayalaxmi Mohanty, Sin L. Tan, S.P.T. Krishnan, and Vladimir B. Bajic. Dragon TF Association Miner: a system for exploring transcription factor associations through text-mining. Nucleic Acids Research, 32:W230–W234, 2004

    Article  Google Scholar 

  20. Carolina Perez-Iratxeta, Peer Bork, and Miguel A. Andrade. Association of genes to genetically inherited diseases using data mining. Nature Genetics, 31(3):316–319, 2002

    Google Scholar 

  21. Wanda Pratt and Meliha Yetisgen-Yildiz. Litlinker: Capturing Connections Across the Biomedical Literature. In Proceedings of the International Conference on Knowledge Capture (K-CAP 2003), pp. 105–112, 2003

    Google Scholar 

  22. Aditya K. Sehgal, Xing Y. Qiu, and Padmini Srinivasan. Mining MEDLINE Metadata to Explore Genes and their Connections. In Proceedings of the 2003 SIGIR Workshop on Text Analysis and Search for Bioinformatics, 2003

    Google Scholar 

  23. Padmini Srinivasan. Text mining: generating hypotheses from MEDLINE. Journal of the American Society for Information Science and Technology (JASIST), 55(5):396–413, 2004

    Article  Google Scholar 

  24. Padmini Srinivasan and Bisharah Libbus. Mining MEDLINE for implicit links between dietary substances and diseases. Bioinformatics, Suppl. 1:I290–I296, 2004

    Google Scholar 

  25. Pang-Ning Tan and Vipin Kumar. Mining Indirect Associations in Web Data. In Proceedings of the Workshop on Mining Logdata Across All Customer Touchpoints (WEBKDD ’01), pp. 145–166, 2001

    Google Scholar 

  26. Nicki Tiffin, Janet F. Kelso, Alan R. Powell, Hong Pan, Vladimir B. Bajic, and Winston A. Hide. Integration of text- and data-mining using ontologies successfully selects disease gene candidates. Nucleic Acids Research, 33(5):1544–1552, 2005

    Article  Google Scholar 

  27. Marc Weeber, Jan A. Kors, and Barend Mons. Online tools to support literature-based discovery in the life sciences. Briefings in Bioinformatics, 6(3):277–286, 2005

    Article  Google Scholar 

  28. Dennis M. Wilkinson and Bernardo A. Huberman. A Method for Finding Communities of Related Genes. In Proceedings of the National Academy of Sciences of the United States of America, 101:5241–5248, 2004

    Google Scholar 

  29. Jonathan D. Wren. The IRIDESCENT System: An Automated Data-Mining Method to Identify, Evaluate, and Analyze Sets of Relationships Within Textual Databases. PhD thesis, University of Texas Southwestern Medical Center, 2003

    Google Scholar 

  30. Jonathan D. Wren, Raffi Bekeredjian, Jelena A. Stewart, Ralph V. Shohet, and Harold R. Garner. Knowledge discovery by automated identification and ranking of implicit relationships. Bioinformatics, 20(3):389–398, 2004

    Article  Google Scholar 

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Sehgal, A.K., Qiu, X.Y., Srinivasan, P. (2008). Analyzing LBD Methods using a General Framework. In: Bruza, P., Weeber, M. (eds) Literature-based Discovery. Information Science and Knowledge Management, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68690-3_6

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  • DOI: https://doi.org/10.1007/978-3-540-68690-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68685-9

  • Online ISBN: 978-3-540-68690-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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