|Science (2003) 302:449-53|
|Northeast Structural Genomics Consortium|
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We have developed an approach using Bayesian networks to predict protein-protein interactions genome-wide in yeast. ...
Our method naturally weights and combines into reliable predictions genomic features only weakly associated with interaction (e.g., messenger RNAcoexpression, coessentiality, and colocalization). In addition to de novo predictions, it can integrate often noisy, experimental interaction data sets. We observe that at given levels of sensitivity, our predictions are more accurate than the existing high-throughput experimental data sets. We validate our predictions with TAP (tandem affinity purification) tagging experiments. Our analysis, which gives a comprehensive view of yeast interactions, is available at genecensus.org/intint.
|metabolism genetics |
|Saccharomyces cerevisiae Proteins RNA-Binding Proteins Saccharomyces cerevisiae DNA Replication Likelihood Functions Nucleosomes RNA, Messenger Sensitivity and Specificity Proteomics Genome, Fungal Protein Interaction Mapping Peptide Chain Elongation, Translational Bayes Theorem DEAD-box RNA Helicases Gene Expression RNA Helicases |
|780 (Last update: 07/22/2017 11:35:48am)|
|Science. 2003 Oct 17;302(5644):449-53.|