Using dependency parsing and probabilistic inference to extract relationships between genes, proteins and malignancies implicit among multiple biomedical research abstracts

ABSTRACT

We describe BioLiterate, a prototype software system which infers relationships involving relationships between genes, proteins and malignancies from research abstracts, and has initially been tested in the domain of the molecular genetics of oncology. The architecture uses a natural language processing module to extract entities, dependencies and simple semantic relationships from texts, and then feeds these features into a probabilistic reasoning module which combines the semantic relationships extracted by the NLP module to form new semantic relationships. One application of this system is the discovery of relationships that are not contained in any individual abstract but are implicit in the combined knowledge contained in two or more abstracts.

References

1. Chan-Goo Kang and Jong C. Park. 2005. Generation of Coherent Gene Summary with Concept-Linking Sentences. Proceedings of the International Symposium on Languages in Biology and Medicine (LBM), pages 41--45, Daejeon, Korea, November, 2005.
2. Claire Nédellec. 2005. Learning Language in Logic - Genic Interaction Extraction Challenge. Proceedings of The 22nd International Conference on Machine Learning, Bonn, Germany.
3. Cliff Goddard. 2002. The On-going Development of the NSM Research Program. Ch 5 (pp. 301--321) of Meaning and Universal Grammar - Theory and Empirical Findings. Volume II. Amsterdam: John Benjamins.
4. Davulcu, H et Al. 2005. IntEx?: A Syntactic Role Driven Protein-Protein Interaction Extractor for Bio-Medical Text. Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics. Detroit.
5. Donaldson, Ian, Joel Martin, Berry de Bruijn, Cheryl Wolting et al. 2003. PreBIND and Textomy - mining the biomedical literature for protein-protein interactions using a support vector machine. BMC Bioinformatics, 4:11,
6. Friedman C, Kra P, Yu H, Krauthammer M, Rzhetsky. 2001. A. GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics Jun;17 Suppl 1:S74--82.
7. Goertzel, Ben and Cassio Pennachin. 2005. Artificial General Intelligence. Springer-Verlag.
8. Goertzel, Ben, Matt Ikle', Izabela Goertzel and Ari Heljakka. 2006. Probabilistic Logic Networks. In preparation.
9. Götz, T and Suhre, O. 2004. Design and implementation of the UIMA Common Analysis System. IBM Systems Journal. V 43, number 3. pages 476--489.
10. Guha, R. V.,&Lenat, D. B. 1994. Enabling agents to work together. Communications of the ACM, 37(7), 127--142.
11. Guha, R. V. and Lenat, D. B. 1990. Cyc: A Midterm Report. AI Magazine 11(3):32--59.
12. Hakenberg,. et al. 2205. LLL'05 Challenge: Genic Interaction Extraction -- Identification of Language Patterns Based on Alignment and Finite State Automata. Proceedings of The 22nd International Conference on Machine Learning, Bonn, Germany. 2005.
13. Hoffmann, R., Valencia, A. 2005. Implementing the iHOP concept for navigation of biomedical literature. Bioinformatics 21(suppl. 2), ii252--ii258 (2005).
14. Ian Niles and Adam Pease. 2001. Towards a Standard Upper Ontology. In Proceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS--2001), Ogunquit, Maine, October 2001
15. Jensen, L. J., Saric, J and Bork, P. 2006. Literature Mining for the biologist: from information retrieval to biological discovery. Nature Reviews. Vol 7. pages 119--129. Natura Publishing Group. 2006.
16. Jing Ding. 2003. Extracting biomedical interactions with from medline using a link grammar parser. Proceedings of 15th IEEE international Conference on Tools With Artificial Intelligence.
17. Kim, Jim-Dong et al. 2004. Introduction to the Bio-NLP Entity Task at JNLPBA 2004. In Proceedings of JNLPBA 2004.
18. Lenat, D., Prakash, M.,&Shepard, M. 1986. CYC: Using common sense knowledge to overcome brittleness and knowledge acquisition bottlenecks. AI Magazine, 6(4), 65--85
19. Lerman, K, McDonal, R., Jin, Y. and Pancoast, E. University of Pennsylvania BioTagger. 2006. http://www.seas.upenn.edu/~ryantm/software/BioTagger/
20. Looks, Moshe, Ben Goertzel and Cassio Pennachin. 2004. Novamente: An Integrative Approach to Artificial General Intelligence. AAAI Symposium on Achieving Human-Level Intelligence Through Integrated Systems and Research, Washington DC, October 2004
21. Mandel, Mark. 2006. Mining the Bibliome. February, 2006 http://bioie.ldc.upenn.edu
22. Mark A. Greenwood, Mark Stevenson, Yikun Guo, Henk Harkema, and Angus Roberts. 2005. Automatically Acquiring a Linguistically Motivated Genic Interaction Extraction System. In Proceedings of the 4th Learning Language in Logic Workshop (LLL05), Bonn, Germany.
23. McDonald, F. Pereira, S. Kulick, S. Winters, Y. Jin and P. White. 2005. Simple Algorithms for Complex Relation Extraction with Applications to Biomedical IE. R. 43rd Annual Meeting of the Association for Computational Linguistics, 2005.
24. Müller, H. M., Kenny, E. E. and Sternberg, P. W. 2004. Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature. PLoS Biol 2(11): e309
25. Pyysalo, S. et al. 2004. Analisys of link Grammar on Biomedical Dependency Corpus Targeted at Protein-Protein Interactions. In Proceedings of JNLPBA 2004.
26. Riedel, et al. 2005. Genic Interaction Extraction with Semantic and Syntactic Chains. Proceedings of The 22nd International Conference on Machine Learning, Bonn, Germany.
27. Ryan McDonald and Fernando Pereira. 2005. Identifying gene and protein mentions in text using conditional random fields. BMC Bioinformatics 2005, 6(Suppl 1):S6
28. Rzhetsky A, Iossifov I, Koike T, Krauthammer M, Kra P, Morris M, Yu H, Duboue PA, Weng W, Wilbur WJ, Hatzivassiloglou V, Friedman C. 2004. Gene-Ways: a system for extracting, analyzing, visualizing, and integrating molecular pathway data. Journal of Biomedical Informatics 37(1):43--53.
29. Sleator, Daniel and Dave Temperley. 1993. Parsing English with a Link Grammar. Third International Workshop on Parsing Technologies, Tilburg, The Netherlands.
30. Smalheiser, N. L and Swanson D. R. 1996. Linking estrogen to Alzheimer's disease: an informatics approach. Neurology 47(3):809--10.
31. Smalheiser, N. L and Swanson, D. R. 1998. Using ARROWSMITH: a computer-assisted approach to formulating and assessing scientific hypotheses. Comput Methods Programs Biomed. 57(3):149--53.
32. Syed Ahmed et al. 2005. IntEx: A Syntactic Role Driven Protein-Protein Interaction Extractor for Bio-Medical Text. Proc. of BioLink '2005, Detroit, Michigan, June 24, 2005
33. Szolovits, Peter. 2003. Adding a medical lexicon to an English parser. Proceedings of 2003 AMIA Annual Symposium. Bethesda. MD.
34. Tanabe, L. U. Scherf, L. H. Smith, J. K. Lee, L. Hunter and J. N. Weinstein. 1999. MedMiner: an Internet Text-Mining Tool for Biomedical Information, with Application to Gene Expression Profiling. BioTechniques 27:1210--1217.
35. Wierzbicka, Anna. 1996. Semantics, Primes and Universals. Oxford University Press.