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| An accurate predictor of genomic PDZ domain interactions would allow the proteomes of organisms to be scanned for potential binders. Such an application would require an accurate and precise predictor to avoid generating too many false positive hits given the large amount of possible interactors in a given proteome. Once validated these predictions will greatly increase the coverage of current PDZ domain interaction networks and further our understanding of the roles that PDZ domains play in a variety of biological processes. | An accurate predictor of genomic PDZ domain interactions would allow the proteomes of organisms to be scanned for potential binders. Such an application would require an accurate and precise predictor to avoid generating too many false positive hits given the large amount of possible interactors in a given proteome. Once validated these predictions will help to increase the coverage of current PDZ domain interaction networks and further our understanding of the roles that PDZ domains play in a variety of biological processes. |
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| The following are SVM proteome scanning predictions for human, fly and worm PDZ domains. The format of the output is: <peptide sequence> <decision value> <validation method> <transcript ids> |
SVM predictions were validated using known interactions from PDZBase, a domain peptide interaction database. The number of interactions which corresponded to known protein protein interactions (PPIs) from iRefIndex (BIND, BioGRID, CORUM, DIP, HPRD, !IntAct, MINT)was also calculated. The following are SVM proteome scanning predictions for human, fly and worm PDZ domains. |
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| * [[attachment:WormSVMPredictions.zip|Worm (zip]] | * [[attachment:WormSVMPredictions.zip|Worm (zip)]] The format of the output is: <predicted binder sequence> <decision value> [PB|IR(.)] <transcript ids> * PB = Found in PDZBase * IR = Corresponds to a PPI in iRefIndex (transcript index1, ..., transcript index n) |
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| * Human Protein Reference Database | * iRefIndex interactions for Human |
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| * Bingo 2.3 * Cytoscape 2.6.3 * Cytoscape-task 2.6.3 |
Proteome scanning of PDZ domain interactions using support vector machines
Contents
Background
An accurate predictor of genomic PDZ domain interactions would allow the proteomes of organisms to be scanned for potential binders. Such an application would require an accurate and precise predictor to avoid generating too many false positive hits given the large amount of possible interactors in a given proteome. Once validated these predictions will help to increase the coverage of current PDZ domain interaction networks and further our understanding of the roles that PDZ domains play in a variety of biological processes.
Results
We built an SVM using mouse and human experimental training data to predict PDZ domain interactions. We showed that it correctly predicts known interactions from proteomes of different organisms and compared to published state of art predictors, is more accurate and precise.
SVM Predictions
SVM predictions were validated using known interactions from PDZBase, a domain peptide interaction database. The number of interactions which corresponded to known protein protein interactions (PPIs) from iRefIndex (BIND, BioGRID, CORUM, DIP, HPRD, IntAct, MINT)was also calculated.
The following are SVM proteome scanning predictions for human, fly and worm PDZ domains.
The format of the output is:
<predicted binder sequence> <decision value> [PB|IR(.)] <transcript ids>
- PB = Found in PDZBase
- IR = Corresponds to a PPI in iRefIndex (transcript index1, ..., transcript index n)
Supplementary
- Models
- Chen model parameter and binding site encoding files
- Stiffler model parameter files
- Proteomes
- Ensembl proteome files for Human, Worm and Fly
- Experiment Interaction files (in peptide file format)
- Fly files from Chen
- Human files from Sidhu
- Mouse files from Stiffler
- Worm files from Chen
- Curated Interaction files (flat files)
- PDZBase for Human (Worm and Fly included, but not used)
- iRefIndex interactions for Human
- Phage codon bias files
- Models
Source Code
- jfreechart 1.0.12 (and dependencies)
- weka 3.9.1
auc calculator (Davis & Goadrich, 2006)
BioJava 1.5
- iText 2.1.3
- jmatio
- Bingo 2.3
- Cytoscape 2.6.3
- Cytoscape-task 2.6.3
- BRAIN 1.0.5 (pdzsvm)
- libSVM 2.8.9 (pdzsvm)
Team
- Shirley Hui
- Gary Bader