|
ABSTRACT
High-quality annotation of biological data is central to bioinformatics. Annotation using terms from ontologies provides reliable computational access to data. The Gene Ontology (GO), a structured controlled vocabulary of nearly 17,000 terms, is becoming the de facto standard for describing the functionality of gene products. Many prominent biomedical databases use GO as a source of terms for functional annotation of their gene-product entries to promote consistent querying and interoperability. However, current annotation editors do not constrain the choice of GO terms users may enter for a given gene product, potentially resulting in an inconsistent or even nonsensical description. Furthermore, the process of annotation is largely an unguided one in which the user must wade through large GO subtrees in search of terms. Relying upon a reasoner loaded with a DAML+OIL version of GO and an instance store of mined GO-term-to-GO-term associations, GOAT aims to aid the user in the annotation of gene products with GO terms by displaying those field values that are most likely to be appropriate based on previously entered terms. This can result in a reduction in biologically inconsistent combinations of GO terms and a less tedious annotation process on the part of the user.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
The Gene Ontology Consortium (2000). Gene Ontology: tool for the unification of biology. Nature Genetics,25: 25--29.
|
| |
2
|
|
| |
3
|
Wroe, C., Stevens, R., Goble, C., and Ashburner, M. (2003). A Methodology to Migrate the Gene Ontology to a Description Logic Environment using DAML+OIL. 2003 Pacific Symposium on Biocomputing Proceedings (PSB), Hawaii, USA, January 2003.
|
| |
4
|
|
| |
5
|
Horrocks, I. (1999). FaCT and iFaCT. In: Lambrix, P., Borgida, A., Lenzerini, M., Möller, R., and Patel-Schneider, P., eds. Proceedings of the International Workshop on Description Logics (DL'99), Linköping, Sweden, July-August 1999.
|
| |
6
|
|
| |
7
|
Camon, E., Magrane, M., Barrell, D., Binns, D., Fleischmann, W., Kersey, P., Mulder, N., Oinn, T., Maslen, J., Cox, A., and Apweiler, R. (2003). The Gene Ontology Annotation (GOA) Project: Implementation of GO in SWISS-PROT, TrEMBL, and InterPro. Genome Research,4, 662--672.
|
| |
8
|
|
| |
9
|
Issel-Tarver, L., Christie, K. R., Dolinski, K., Andrada, R., Balakrishnan, R., Ball, C. A., Binkley, G., Dong, S., Dwight, S. S., Fisk, D. G., Harris, M., Schroeder, M., Sethuraman, A., Tse, K., Weng, S., Botstein, D., and Cherry, J. M. (2002). Saccharomyces Genome Database. Methods of Enzymology,350, 329--346.
|
| |
10
|
Raychaudhuri, S., Chang, J. T., Sutphin, P. D., and Altman, R. B. (2002). Associating genes with gene ontology codes using a maximum entropy analysis of biomedical literature. Genome Research,12, 203--214.
|
| |
11
|
Hennig, S., Groth, D., and Lehrach, H. (2003). Automated Gene Ontology annotation for anonymous sequence data. Nucleic Acids Research,31 (13), 3712--3715.
|
| |
12
|
Hvidsten, T. R., Komorowski, J., Sandvik, A. K., and Laegreid, A. (2001). Predicting gene function from gene expressions and ontologies. 2001 Pacific Symposium on Biocomputing Proceedings (PSB), Hawaii, USA, 299--310.
|
| |
13
|
King, O. D., Foulger, R. E., Dwight, S. S., White, J. V., and Roth, F. R. (2003). Predicting Gene Function From Patterns of Annotation. Genome Research,13, 896--904.
|
| |
14
|
|
|