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Using protein complexes to predict phenotypic effects of gene mutation
BACKGROUND: Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. RESULTS: Using a wide range of functional genomic data from the yeast Saccharomyce...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2258176/ https://www.ncbi.nlm.nih.gov/pubmed/18042286 http://dx.doi.org/10.1186/gb-2007-8-11-r252 |
Sumario: | BACKGROUND: Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes. RESULTS: Using a wide range of functional genomic data from the yeast Saccharomyces cerevisiae, we show that the best predictor of a protein's knockout phenotype is the knockout phenotype of other proteins that are present in a protein complex with it. Even the addition of multiple datasets does not improve upon the predictions made from protein complex membership. Similarly, we find that a proxy for protein complexes is a powerful predictor of disease phenotypes in humans. CONCLUSION: We propose that identifying human protein complexes containing known disease genes will be an efficient method for large-scale disease gene discovery, and that yeast may prove to be an informative model system for investigating, and even predicting, the genetic basis of both Mendelian and complex disease phenotypes. |
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