| Autor: |
Yan H; Department of Cancer Biology, Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America., Venkatesan K, Beaver JE, Klitgord N, Yildirim MA, Hao T, Hill DE, Cusick ME, Perrimon N, Roth FP, Vidal M |
| Jazyk: |
angličtina |
| Zdroj: |
PloS one [PLoS One] 2010 Aug 12; Vol. 5 (8), pp. e12139. Date of Electronic Publication: 2010 Aug 12. |
| DOI: |
10.1371/journal.pone.0012139 |
| Abstrakt: |
Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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