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Development of Compendium for Esophageal Squamous Cell Carcinoma

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Gene Ontology annotations at SGD: new data sources and annotation methods.

Eurie L Hong¹, Rama Balakrishnan, Qing Dong

¹Department of Genetics, Stanford University, Stanford, CA, USA.

Nucleic Acids Research

|November 6, 2007

Summary

The Saccharomyces Genome Database now integrates high-throughput experiments and computational predictions for yeast gene products. This expansion enhances Gene Ontology annotations, especially for uncharacterized genes, improving data accuracy and completeness.

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Area of Science:

Yeast genomics and bioinformatics
Functional genomics and annotation
Computational biology

Background:

The Saccharomyces Genome Database (SGD) is a primary resource for budding yeast Saccharomyces cerevisiae information.
Gene Ontology (GO) annotations traditionally rely on published experimental data.
High-throughput experiments and computational predictions offer valuable data, particularly for understudied genes.

Purpose of the Study:

To enhance the Saccharomyces Genome Database (SGD) with diverse data sources for Gene Ontology (GO) annotations.
To distinguish between different data sources and annotation methods within SGD.
To improve the comprehensiveness and accuracy of GO annotations for yeast genes.

Main Methods:

Integration of high-throughput experimental data into SGD.
Inclusion of computational predictions from the GO Annotation Project (GOA UniProt).
Modification of SGD resources to differentiate annotation sources and methods.

Main Results:

SGD now provides GO annotations derived from high-throughput data and computational predictions.
SGD resources are updated to clearly indicate the origin and type of GO annotation data.
Enhanced ability to compare SGD annotations with independent sources.

Conclusions:

The expanded SGD GO annotation resource offers a more complete view of yeast gene functions.
Distinguishing data sources aids users in evaluating annotation evidence.
The integrated data supports ongoing curation and identification of novel gene functions.