Classifying protein-protein interaction articles using word and syntactic features

BMC Bioinformatics

Volumn 12, Issue SUPPL. 8, 2011, Pages

  Kim, Sun ^a   Wilbur, W J ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL NETWORKS; BIOMEDICAL LITERATURE; GRAMMATICAL RELATIONS; LARGE MARGIN CLASSIFIERS; MACHINE LEARNING APPROACHES; PROTEIN-PROTEIN INTERACTIONS; RANKING PERFORMANCE; SYNTACTIC INFORMATION;

COMPLEX NETWORKS; FUNCTION EVALUATION; SEARCH ENGINES; SYNTACTICS;

PROTEINS;

PROTEIN;

ALGORITHM; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; DATA MINING; METABOLISM; PROTEIN ANALYSIS; PROTEIN DATABASE;

ALGORITHMS; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; DATA MINING; DATABASES, PROTEIN; PROTEIN INTERACTION MAPPING; PROTEINS;

EID: 80053411166     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-S8-S9     Document Type: Article

References (32)

1. Bader GD, Donaldson I, Wolting C, Ouellette BFF, Pawson T, Hogue CWV. BIND-the Biomolecular Interaction Network Database. Nucleic Acids Research 2003, 31:248-250. 10.1093/nar/gkg056, 165503, 12519993.
2. Ceol A, Aryamontri AC, Licata L, Peluso D, Briganti L, Perfetto L, Castagnoli L, Cesareni G. MINT, the molecular interaction database: 2009 update. Nucleic Acids Research 2010, 38:D532-D539. 10.1093/nar/gkp983, 2808973, 19897547.
3. Aranda B, Achuthan P, Alam-Faruque Y, Armean I, Bridge A, Derow C, Feuermann M, Ghanbarian AT, Kerrien S, Khadake J, Kerssemakers J, Leroy C, Menden M, Michaut M, Montecchi-Palazzi L, Neuhauser SN, Orchard S, Perreau V, Roechert B, van Eijk K, Hermjakob H. The IntAct molecular interaction database in 2010. Nucleic Acids Research 2010, 38:D525-D531. 10.1093/nar/gkp878, 2808934, 19850723.
4. Salwinski L, Miller CS, Smith AJ, Pettit FK, Bowie JU, Eisenberg D. The Database of Interacting Proteins: 2004 update. Nucleic Acids Research 2004, 32:D449-D451. 10.1093/nar/gkh086, 308820, 14681454.
5. Blaschke C, Leon EA, Krallinger M, Valencia A. Evaluation of BioCreAtIvE assessment of task 2. BMC Bioinformatics 2005, 6(Suppl 1):16. 10.1186/1471-2105-6-S1-S16, 1869008, 15960828.
6. Krallinger M, Morgan A, Smith L, Leitner F, Tanabe L, Wilbur J, Hirschman L, Valencia A. Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge. Genome Biology 2008, 9(Suppl 2):S1. 10.1186/gb-2008-9-s2-s1, 2559980, 18834487.
7. Donaldson I, Martin J, de Brujin B, Wolting C, Lay V, Tuekam B, Zhang S, Baskin, Bader GD, Michalickova K, Pawson T, Hogue CWV. PreBIND and Textomy - mining the biomedical literature for protein-protein interactions using a support vector machine. BMC Bioinformatics 2003, 4(11). 153503, 12689350.
8. Mitsumort T, Murata M, Fukuda Y, Doi K, Doi H. Extracting protein-protein interaction information from biomedical text with SVM. IEICE Transaction on Information and Systems 2006, E89-D(8):2464-2466.
9. Sugiyama K, Hanato K, Yoshikawa M, Uemura S. Extracting information on protein-protein interactions from biological literature based on machine learning approaches. Genome Informatics 2003, 14:699-700.
10. Björne J, Ginter F, Pyysalo S, Tsujii J, Salakoski T. Complex event extraction at PubMed scale. Bioinformatics 2010, 26:i382-i390. 10.1093/bioinformatics/btq180, 2881365, 20529932.
11. Buyko E, Hahn U. Evaluating the impact of alternative dependency graph encodings on solving event extraction tasks. Proceedings of the Conference on Empirical Methods in Natural Language Processing: 9-11 October 2010; Cambridge 2010, 982-992.
12. Jang H, Lim J, Lim JH, Park SJ, Lee KC, Park SH. Finding the evidence for protein-protein interactions from PubMed abstracts. Bioinformatics 2006, 22:e220-e226. 10.1093/bioinformatics/btl203, 16873475.
13. Kim S, Shin SY, Lee IH, Kim SJ, Sriram R, Zhang BT. PIE: an online prediction system for protein-protein interactions from text. Nucleic Acids Research 2008, 36:W411-W415. 10.1093/nar/gkn281, 2447724, 18508809.
14. Miyao Y, Sagae K, Sætre R, Matsuzaki T, Tsujii J. Evaluating contributions of natural language parsers to protein-protein interaction extraction. Bioinformatics 2009, 25:394-400. 10.1093/bioinformatics/btn631, 2639072, 19073593.
15. Krallinger M, Vazquez M, Leitner F, Valencia A. Results of the BioCreative III (interaction) article classification task. Proceedings of the BioCreative III: 13-15 September 2010; Bethesda 2010, 17-23.
16. Kim S, Wilbur WJ. Improving protein-protein interaction article classification performance by utilizing grammatical relations. Proceedings of the BioCreative III: 13-15 September 2010; Bethesda 2010, 83-88.
17. Tanabe L, Wilbur WJ. A priority model for named entities. Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology: 4-9 June 2006; New York 2006, 33-40.
18. Huang M, Ding S, Wang H, Zhu X. Mining physical protein-protein interactions from the literature. Genome Biology 2008, 9(Suppl 2):S12. 10.1186/gb-2008-9-s2-s12, 2559983, 18834490.
19. Lowe HJ, Barnett GO. Understanding and using the medical subject headings (MeSH) vocabulary to perform literature searches. The Journal of the Americal Medical Association 1994, 271(14):1103-1108.
20. Curran JR, Clark S, Bos J. Linguistically motivated large-scale NLP with C&C and Boxer. Proceedings of the ACL 2007 Demonstrations Session (ACL-07 demo): 23-30 June 2007; Prague 2007, 33-36.
21. Ando RK. BioCreative II gene mention tagging system at IBM Watson. Proceedings of the Second BioCreative Challenge Evaluation Workshop: 23-25 April 2007; Madrid 2007, 101-103.
22. Zhang T. Solving large scale linear prediction problems using stochastic gradient descent algorithms. Proceedings of the 21st International Conference on Machine Learning: 4-8 July 2004; Banff 2004, 919-926.
23. Baldi P, Brunak S, Chauvin Y, Andersen CAF, Nielsen H. Assessing the accuracy of prediction algorithms for classification: an overview. Bioinformatics 2000, 16(5):412-424. 10.1093/bioinformatics/16.5.412, 10871264.
24. Porter MF. An algorithm for suffix stripping. Program 1980, 14(3):130-137.
25. Kubat M, Matwin S. Addressing the curse of imbalanced training sets: one-sided selection. Proceedings of the 14th International Conference on Machine Learning: 8-12 July 1997; Nashville 1997, 179-186.
26. Batista GEAPA, Prati RC, Monard MC. A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explorations 2004, 6:20-29.
27. Settles B. Active learning literature survey. Tech. Rep. 1648 2010, University of Wisconsin-Madison.
28. Nash S, Nocedal J. A numerical study of the limited memory BFGS method and the truncated-Newton method for large scale optimization. SIAM Journal on Optimization 1991, 1(3):358-372.
29. Niu Y, Otasek D, Jurisica I. Evaluation of linguistic features useful in extraction of interactions from PubMed; application to annotating known, high-throughput and predicted interactions in I2D. Bioinformatics 2010, 26:111-119. 10.1093/bioinformatics/btp602, 2796811, 19850753.
30. Rebholz-Schuhmann D, Jimeno-Yepes A, Arregui M, Kirsch H. Measuring prediction capacity of individual verbs for the identification of protein interactions. Journal of Biomedical Informatics 2010, 43(2):200-207. 10.1016/j.jbi.2009.09.007, 19818874.
31. Smith LH, Wilbur WJ. Finding related sentence pairs in MEDLINE. Information Retrieval 2010, 13(6):601-617. 10.1007/s10791-010-9126-8, 2992462, 21170415.
32. Vapnik VN. Statistical Learning Theory. 1998, Springer.