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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. | SVM predictions were validated using known interactions from PDZBase, a domain peptide interaction database. To further support our predictions, the number of interactions which also corresponded to known protein-protein interactions (PPIs) was calculated for 213 PDZ domains with interactions from iRefIndex. iRefIndex is a PPI database which consolidates PPIs from different databases including BIND, BioGRID, CORUM, DIP, HPRD, !IntAct, MINT. |
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The following are SVM proteome scanning predictions for 192 human PDZ domains for which the SVM predicted binders. From this set 75 PDZ domains had predicted interactions which corresponded to PPIs in iRefIndex. Please see Supplemental Information for the identities of these domains. | The following are SVM proteome scanning predictions for 192 human PDZ domains for which the SVM predicted binders. From this set 75 PDZ domains had predicted interactions which corresponded to PPIs in iRefIndex. Please see Supplementary Information for more details. |
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. To further support our predictions, the number of interactions which also corresponded to known protein-protein interactions (PPIs) was calculated for 213 PDZ domains with interactions from iRefIndex. iRefIndex is a PPI database which consolidates PPIs from different databases including BIND, BioGRID, CORUM, DIP, HPRD, IntAct, MINT.
The following are SVM proteome scanning predictions for 13 human, 6 fly and 6 worm PDZ domains with domain-peptide interactions in PDZBase.
The following are SVM proteome scanning predictions for 192 human PDZ domains for which the SVM predicted binders. From this set 75 PDZ domains had predicted interactions which corresponded to PPIs in iRefIndex. Please see Supplementary Information for more details.
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
ProteomeScan Files
Files required to run the ProteomeScan software
- 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