Chapter title |
Community-Wide Evaluation of Computational Function Prediction
|
---|---|
Chapter number | 10 |
Book title |
The Gene Ontology Handbook
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-3743-1_10 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3741-7, 978-1-4939-3743-1
|
Authors |
Iddo Friedberg, Predrag Radivojac |
Editors |
Christophe Dessimoz, Nives Škunca |
Abstract |
A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, to gain insights into the activity of these molecules and guide experiments, we must rely on computational means to functionally annotate the majority of sequence data. To understand how well these algorithms perform, we have established a challenge involving a broad scientific community in which we evaluate different annotation methods according to their ability to predict the associations between previously unannotated protein sequences and Gene Ontology terms. Here we discuss the rationale, benefits, and issues associated with evaluating computational methods in an ongoing community-wide challenge. |
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Demographic breakdown
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Researcher | 7 | 18% |
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Professor | 2 | 5% |
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Mathematics | 1 | 3% |
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