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## page was renamed from Software/DomPep #acl All:read = Predicting physiologically relevant SH3 domain mediated protein-protein interactions in yeast = Shobhit Jain and Gary Bader == Motivation == Many intracellular signaling processes are mediated by interactions involving peptide recognition modules such as SH3 domains. These domains bind to small, contiguous sequence motifs which can be identified using high-throughput experimental screens such as phage display and then used to computationally predict protein interactions mediated by these domains. Most protein-protein interaction prediction approaches either lack the ability to predict peptide recognition module mediated interactions or they do not consider different constraints governing physiologically relevant interactions between two proteins. == Results == A novel method for predicting physiologically relevant SH3 domain-peptide mediated protein-protein interactions in S. cerevisae using phage display data is presented. This method is based on the fact that domain-peptide mediated interactions do not occur in isolation. They are influenced by many sequential and cellular constraints. Therefore, by combining different peptide and protein features using multiple Bayesian models we are able to predict high confidence interactions with an overall accuracy (F-score) between 0.98 and 0.96 for different thresholds. == Downloads == ==== Latest Release ==== Source: [[attachment:DoMo-Pred.zip]] <BR> Binary: [[attachment:DoMo-Pred-Binary.zip]] ==== Datasets ==== ==== Predictions ==== [[attachment:predictions.zip]] ==== Supplementary material ==== [[attachment:supplementary.pdf]] |
Predicting physiologically relevant SH3 domain mediated protein-protein interactions in yeast
Shobhit Jain and Gary Bader
Motivation
Many intracellular signaling processes are mediated by interactions involving peptide recognition modules such as SH3 domains. These domains bind to small, contiguous sequence motifs which can be identified using high-throughput experimental screens such as phage display and then used to computationally predict protein interactions mediated by these domains. Most protein-protein interaction prediction approaches either lack the ability to predict peptide recognition module mediated interactions or they do not consider different constraints governing physiologically relevant interactions between two proteins.
Results
A novel method for predicting physiologically relevant SH3 domain-peptide mediated protein-protein interactions in S. cerevisae using phage display data is presented. This method is based on the fact that domain-peptide mediated interactions do not occur in isolation. They are influenced by many sequential and cellular constraints. Therefore, by combining different peptide and protein features using multiple Bayesian models we are able to predict high confidence interactions with an overall accuracy (F-score) between 0.98 and 0.96 for different thresholds.
Downloads
Latest Release
Source: DoMo-Pred.zip <BR> Binary: DoMo-Pred-Binary.zip
Datasets
Predictions