Gene functional annotation by statistical analysis of biomedical articles

International Journal of Medical Informatics

Volumn 76, Issue 8, 2007, Pages 601-613

  Theodosiou, T ^a   Angelis, L ^a   Vakali, A ^a   Thomopoulos, G N ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Classification; Gene ontology; Genes annotation; Linear discriminant analysis; Text mining

Indexed keywords

FUNCTIONAL ANALYSIS; GENES; ONTOLOGY; STATISTICAL METHODS; SUPPORT VECTOR MACHINES;

BIOCHEMICAL PATHWAYS; GENES ANNOTATION; LINEAR DISCRIMINANT ANALYSIS; LINEAR DISCRIMINANT ANALYSIS (LDA); TEXT MINING;

BIOMEDICAL ENGINEERING;

ARTICLE; DATA BASE; GENE FUNCTION; INFORMATION PROCESSING; MEDICAL INFORMATION; MEDICAL LITERATURE; MEDICAL RESEARCH; MOLECULAR BIOLOGY; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

ABSTRACTING AND INDEXING; ARTIFICIAL INTELLIGENCE; BIOMEDICAL RESEARCH; DATABASES, BIBLIOGRAPHIC; DISCRIMINANT ANALYSIS; GENES; PEER REVIEW, RESEARCH; REPRODUCIBILITY OF RESULTS;

EID: 34249906427     PISSN: 13865056     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijmedinf.2006.04.011     Document Type: Article

References (43)

1. Ashburner M., Ball C., Blake J., Botstein D., Butler H., Cherry J., Davis A., Dolinski K., Dwight S., Eppig J., Harris M., Hill D., Issel-Tarver L., Kasarskis A., Lewis S., Matese J., Richardson J., Ringwald M., Rubin G., and Sherlock G. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25 1 (2000) 25-29. http://dx.doi.org/10.1038/75556
2. Consortium G.O. Creating the gene ontology resource: design and implementation. Genome Res. 11 8 (2001) 1425-1433
3. Karp P.D., Riley M., Saier M., Paulsen I.T., Collado-Vides J., Paley S.M., Pellegrini-Toole A., sar Bonavides, and Gama-Castro S. The EcoCyc database. Nucleic Acids Res. 30 1 (2002) 56-58
4. Camon E., Magrane M., Barrell D., Binns D., Fleischmann W., Kersey P., Mulder N., Oinn T., Maslen J., Cox A., and Apweiler R. The Gene Ontology Annotation (GOA) project: implementation of GO in SWISS-PROT, TrEMBL, and InterPro. Genome Res. 13 4 (2003) 662-672. http://dx.doi.org/10.1101/gr.461403
5. Dwight S.S., Harris M.A., Dolinski K., Ball C.A., Binkley G., Christie K.R., Fisk D.G., Issel-Tarver L., Schroeder M., Sherlock G., Sethuraman A., Weng S., Botstein D., and Cherry J.M. Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO). Nucleic Acids Res. 30 1 (2002) 69-72
6. Xie H., Wasserman A., Levine Z., Novik A., Grebinskiy V., Shoshan A., and Mintz L. Largescale protein annotation through gene ontology. Genome Res. 12 5 (2002) 785-794. http://dx.doi.org/10.1101/gr.86902
7. PubMed, National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institute of Health (NIH), http://www.pubmed.com.
8. Raychaudhuri S., Chang J.T., Sutphin P.D., and Altman R.B. Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature. Genome Res. 12 1 (2002) 203-214. http://dx.doi.org/10.1101/gr.199701
9. Wheeler D.L., Church D.M., Edgar R., Federhen S., Helmberg W., Madden T.L., Pontius J.U., Schuler G.D., Schriml L.M., Sequeira E., Suzek T.O., Tatusova T.A., and Wagner L. Database resources of the National Center for Biotechnology Information: update. Nucleic Acids Res. 32 (2004) D35-D40. http://dx.doi.org/10.1093/nar/gkh073 (Database issue)
10. de Bruijn B., and Martin J. Getting to the (c)ore of knowledge: mining biomedical literature. Int. J. Med. Inform. 67 1-3 (2002) 7-18
11. Khan S., Situ G., Decker K., and Schmidt C.J. GoFigure: automated Gene Ontology annotation. Bioinformatics 19 18 (2003) 2484-2485
12. Martin D.M., Berriman M., and Barton G.J. GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes. BMC Bioinform. 5 (2004) 178
13. Andrade M., and Valencia A. Automatic annotation for biological sequences by extraction of keywords from MEDLINE abstracts. Development of a prototype system. Proc. Int. Conf. Intell. Syst. Mol. Biol. 5 (1997) 25-32
14. Shatkay H., Edwards S., Wilbur W., and Boguski M. Genes, themes and microarrays: using information retrieval for large-scale gene analysis. Proc. Int. Conf. Intell. Syst. Mol. Biol. 8 (2000) 317-328
15. Tamames J., Ouzounis C., Casari G., Sander C., and Valencia A. EUCLID: automatic classification of proteins in functional classes by their database annotations. Bioinformatics 14 6 (1998) 542-543
16. Eisenhaber F., and Bork P. Evaluation of human-readable annotation in biomolecular sequence databases with biological rule libraries. Bioinformatics 15 7-8 (1999) 528-535
17. Vinayagam A., Knig R., Moormann J., Schubert F., Eils R., Glatting K.H., and Suhai S. Applying support vector machines for Gene Ontology based gene function prediction. BMC Bioinform. 5 1 (2004) 116. http://dx.doi.org/10.1186/1471-2105-5-116
18. Hennig S., Groth D., and Lehrach H. Automated Gene Ontology annotation for anonymous sequence data. Nucleic Acids Res. 31 13 (2003) 3712-3715
19. T. Izumitani, H. Taira, H. Kazawa, E. Maeda, Assigning gene ontology categories (go) to yeast genes using text-based supervised learning methods, in: Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference (CSB 2004), 2004, pp. 503-504.
20. Christie K.R., Weng S., Balakrishnan R., Costanzo M.C., Dolinski K., Dwight S.S., Engel S.R., Feierbach B., Fisk D.G., Hirschman J.E., Hong E.L., Issel-Tarver L., Nash R., Sethuraman A., Starr B., Theesfeld C.L., Andrada R., Binkley G., Dong Q., Lane C., Schroeder M., Botstein D., and Cherry J.M. Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms. Nucleic Acids Res. 32 (2004) D311-D314. http://dx.doi.org/10.1093/nar/gkh033 (Database issue)
21. Lim T., Loh W., and Shih Y. A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Machine Learn. 40 3 (2000) 203-228
22. D. Meyer, F. Leisch, K. Hornik, Benchmarking support vector machines, Tech. Rep. 78, Vienna University of Economics and Business Administration in cooperation with University of Vienna, Vienna University of Technology, 2002.
23. Krzanowski W.J. Principles of Multivariate Analysis. A User's Perspective (1988), Oxford Science Publications
24. In: Bean C.A., and Green R. (Eds). Relationships in the Organization of Knowledge (2001), Kluwer Academic Publishers, NY 171-184
25. Perez-Iratxeta C., Bork P., and Andrade M. Association of genes to genetically inherited diseases using data mining. Nat. Genet. 31 (2002) 316-319
26. Salton G. Automatic text analysis. Science 168 (1970) 335-343
27. Shatkay H., and Feldman R. Mining the biomedical literature in the genomic era: an overview. J. Comput. Biol. 10 6 (2003) 821-855. http://dx.doi.org/10.1089/106652703322756104
28. Manning C.D., and Schutze H. Foundations of Statistical Natural Language Processing (1999), The MIT Press
29. J.M. Daniel Jurafsky, Speech and natural language processing, Alan Apt., 2000, ISBN 0-13-095069-6.
30. Paice C. Another stemmer. SIGIR Forum 24 3 (1990) 56-61
31. Zobel J., and offat A.M. Exploring the similarity space. SIGIR Forum 32 1 (1998) 18-34
32. W.N. Venables, B. D. Ripley, Modern Applied Statistics with S. Fourth Edition, fourth ed., Springer, 2002, ISBN 0-387-95457-0.
33. Cortes C., and Vapnik V. Support-vector networks. Machine Learn. 20 (1995) 273-297
34. Baldi P., Frasconi P., and Smyth P. Modeling the Internet and the Web (2003), John Wiley and Sons Ltd
35. Fisher R.A. The use of multiple measurements in taxonomic problem. Ann. Eugenices 7 (1936) 179-188
36. Lattin J., Carroll D., and Green P. Analyzing multivariate data. Curt. Hinrichs (2003)
37. Tabachnick B.G., and Fidell L.S. Using Mutlivariate Statistics (2001), Allyn and Bacon. 0-321-05677-9
38. Hair J.F., Anderson R.E., Tatham R.L., and Black W.C. Mutlivariate Data Analysis. fifth ed. (1998), Prentice Hall PTR. 0-13-930587-4
39. Cleveland W.S. Visualizing Data (1993), Hobart Press
40. Andrews D.F. Plots of high-dimensional data. Biometrics 28 (1972) 125-136
41. Van Rijsbergen C.J. Information Retrieval. second ed. (1979), Department of Computer Science, University of Glasgow
42. R Development Core Team, R: a language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, 2004, ISBN 3-900051-00-3, URL http://www.R-project.org.
43. C.-C. Chang, C.-J. Lin, LIBSVM: a library for support vector machines, 2001, software available at http://www.csie.ntu.edu.tw/∼cjlin/libsvm.