Ontologies and Functional Genomics

Data Analysis and Visualization in Genomics and Proteomics

Volumn , Issue , 2005, Pages 99-112

  Al Shahrour, Fátima ^a   Dopazo, Joaquín ^a,b  

^a Centro Nacional de Investigaciones Oncológicas   (Spain)

^b Bioinformatics Unit   (Spain)

Author keywords

Annotation; Bio ontologies; FatiGO (Fast Assignment and Transference of Information using GO); Functional genomics; Gene ontology; Information mining; Multiple testing; Onto express

Indexed keywords

EID: 84889826091     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/0470094419.ch7     Document Type: Chapter

References (42)

1. Al-Shahrour, F., Díaz-Uriarte, R. and Dopazo, J. (2004) FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes. Bioinformatics, 20, 578-580.
2. Al-Shahrour, F., Herrero, J., Mateos, Á., Santoyo, J., Díaz-Uriarte, R. and Dopazo, J. (2003) Using Gene Ontology on genome-scale studies to find significant associations of biologically relevant terms to group of genes. Neural Networks for Signal Processing XIII. IEEE Press, New York, 43-52 (see technical report in http://bioinfo.cnio.es/docus/papers/techreports.html#FatiGO-NNSP).
3. Ashburner, M., Ball, C. A., Blake, J. A. et al. (2000) Gene Ontology: tool for the unification of biology. Nat Genet, 25, 25-29.
4. Bard, J. B. and Rhee, S. Y. (2004) Ontologies in biology: design, applications and future challenges. Nat Rev Genet, 5, 213-322.
5. Bassett, D. E., Eisen, M. B. and Boguski, M. S. (1999) Gene expression informatics-it's all in your mine. Nat Genet, 21, 51-55.
6. Beissbarth T., Speed T. (2004) GOstat: find statistically overrepresented Gene Ontologies within a group of genes. Bioinformatics, in press.
7. Benjamini, Y. and Hochberg, Y. (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc, B 57, 289-300.
8. Benjamini, Y. and Yekutieli, D. (2001) The control of the false discovery rate in multiple testing under dependency. Ann Stat, 29,1165-1188.
9. Blaschke, C., Hirschman, L., Valencia, A. (2002) Information extraction in molecular biology. Briefings Bioinformatics, 3, 154-165.
10. Camon, E., Magrane, M., Barrell, D. et al. (2003) The Gene Ontology Annotation (GOA) project: implementation of GO in SWISS-PROT, TrEMBL, and InterPro. Genome Res, 3, 662-672.
11. Castillo-Davis, C. I. and Hartl, D. L. (2003) GeneMerge-post-genomic analysis, data mining and hypothesis testing. Bioinformatics, 19, 891-892.
12. DeRisi, J. L., Iyer, V. R. and Brown, P. O. (1997) Exploring the metabolic and genetic control of gene expression on a genomic scale. Science, 278, 680-686.
13. Díaz-Uriarte, R., Al-Shahrour, F. and Dopazo, J. (2003) Use of GO terms to understand the biological significance of microarray differential gene expression data. In Microarray Data Analysis III, eds. K. F. Johnson and S. M. Lin. Kluwer, Dodrecht, 233-247.
14. Doniger, S.W., Salomonis, N., Dahlquist, K. D., Vranizan K., Lawlor, S. C. and Conklin, B. R. (2003) MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biology, 4, R7.
15. Dopazo, J. and Carazo, J. M. (1997). Phylogenetic reconstruction using a growing neural network that adopts the topology of a phylogenetic tree. J. Mol. Evol, 44, 226-233.
16. Eisen, M., Spellman, P. L., Brown, P. O. and Botsein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA, 95, 14863-14868.
17. Ge, H., Walhout, A. J., Vidal, M. (2003) Integrating 'omic' information: a bridge between genomics and systems biology. Trends Genet, 19, 551-560.
18. Herrero, J., Al-Shahrour, F., Díaz-Uriarte, R., Mateos, A., Vaquerizas, J. M., Santoyo, J. and Dopazo, J. (2003) GEPAS, a web-based resource for microarray gene expression data analysis. Nucleic Acids Res, 31, 3461-3467.
19. Herrero, J., Valencia, A. and Dopazo, J. (2001) A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics, 17, 126-136.
20. Holloway, A. J., van Laar, R. K., Tothill, R. W., Bowtell, D. D. (2002) Options available-from start to finish-for obtaining data from DNA microarrays II. Nat Genet. 32 (Suppl.), 481-489.
21. Jensen, L. J., Gupta, R., Staerfeldt, H. H., Brunak, S. (2003) Prediction of human protein function according to Gene Ontology categories. Bioinformatics, 19, 635-642.
22. Jenssen, T.-K., Laegreid, A., Komorowski, J. Hovig, E. (2000) A literature network of human genes for high-throughput analysis of gene expression. Nature Genet, 28, 21-28.
23. Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y., Hattori, M. (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res, 32 (database issue), D277-D280.
24. Khatri, P., Draghici, S., Ostermeier, G. C. and Krawetz, S. A. (2002). Profiling gene expression using onto-express. Genomics, 79, 1-5.
25. MacBeath, G. (2002) Protein microarrays and proteomics. Nat Genet. 32, (Suppl). 526-532.
26. Mateos, Á., Dopazo, J., Jansen, R., Tu, Y., Gerstein, M. and Stolovitzky, G. (2002) Systematic learning of gene functional classes from DNA array expression data by using multilayer perceptrons. Genome Res, 12, 1703-1715.
27. Mootha, V. K., Lindgren, C. M., Eriksson, K. F., et al. (2003) PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet, 34, 267-273.
28. Mulder, N. J., Apweiler, R., Attwood, T. K., et al. (2003) The InterPro Database, 2003 brings increased coverage and new features. Nucleic Acids Res, 31, 315-318.
29. Oliveros, J. C., Blaschke, C., Herrero, J., Dopazo, J., Valencia, A. (2000) Expression profiles and biological function. Genome Informatics, 10, 106-117.
30. Pavlidis, P., Lewis, D. P., and Noble, W. S. (2002) Exploring gene expression data with class scores. Pacific Symp. Biocomput, 7, 474-485.
31. Raychaudhuri, S, Chang, J. T., Imam, F., Altman, R. B. (2003) The computational analysis of scientific literature to define and recognize gene expression clusters. Nucleic Acids Res, 31, 4553-4560.
32. Raychaudhuri, S., Chang, J. T., Sutphin, P. D., Altman, R. B. (2002) Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature. Genome Res, 12, 203-214.
33. Raychaudhuri, S., Schutze, H., Altman, R. B. (2002) Using text analysis to identify functionally coherent gene groups. Genome Res, 12, 1582-1590.
34. Robinson, M. D., Grigull, J., Mohammad, N. and Hughes, T. R. (2002). FunSpect: a web-based cluster interpreter for yeast. BMC Bioinformatics, 3, 1-5.
35. Schug, J., Diskin, S., Mazzarelli, J., Brunk, B. P., Stoeckert, C. J. Jr. (2002) Predicting gene ontology functions from ProDom and CDD protein domains. Genome Res, 12, 648-655.
36. Shah, N. H., Fedoroff, N. V. (2004) CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology. Bioinformatics, 20, 1196-1197.
37. Tanabe, L., Smith, L. H., Lee, J. K., Scherf, U., Hunter, L., Weinstein, J. N. (1999) MedMiner: an internet tool for filtering and organizing bio-medical information, with application to gene expression profiling. BioTechniques, 27, 1210-1217.
38. van Noort, V., Snel, B. and Huynen M. A. (2003) Predicting gene function by conserved coexpression. Trends Genet 19, 238-242.
39. Westfall, P. H. and Young, S. S. (1993) Resampling-Based Multiple Testing. Wiley, New York.
40. Xenarios, I., Salwinski, L., Duan, X. J., Higney, P., Kim, S., Eisenberg D. 2002 DIP: the Database of Interacting Proteins. A research tool for studying cellular networks of protein interactions. Nucl. Acids Res, 30, 303-305.
41. Xie, H.,Wasserman, A., Levine, Z., Novik, A., Grebinskiy, V., Shoshan, A., Mintz, L. (2002) Largescale protein annotation through gene ontology. Genome Res, 2, 785-794.
42. Zeeberg, B. R., Feng,W.,Wang, G., et al. (2003) GoMiner: a resource for biological interpretation of genomic and proteomic data. Genome Biology, 4 (4), R28.