| Autor: |
Han Yan, Kavitha Venkatesan, John E Beaver, Niels Klitgord, Muhammed A Yildirim, Tong Hao, David E Hill, Michael E Cusick, Norbert Perrimon, Frederick P Roth, Marc Vidal |
| Jazyk: |
angličtina |
| Rok vydání: |
2010 |
| Předmět: |
|
| Zdroj: |
PLoS ONE, Vol 5, Iss 8, p e12139 (2010) |
| Druh dokumentu: |
article |
| ISSN: |
1932-6203 |
| DOI: |
10.1371/journal.pone.0012139 |
| Popis: |
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: |
Directory of Open Access Journals |
| Externí odkaz: |
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