Research article
Disease candidate gene identification and prioritization using protein interaction networks
-
* Corresponding author: Anil G Jegga Anil.Jegga@cchmc.org
1 Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
2 Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, USA
3 Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
BMC Bioinformatics 2009, 10:73 doi:10.1186/1471-2105-10-73
Published: 27 February 2009Additional files
Additional file 1:
Venn diagrams of unique genes and interactions from the three (BIND, BioGRID, and HPRD) PPIN data source.
Format: PDF Size: 14KB Download file
This file can be viewed with: Adobe Acrobat Reader
Additional file 2:
Training set data used for evaluation of PPIN in disease candidate gene prioritization, comprising 19 diseases with 693 associated genes. Of these, 589 genes were used in the cross validation because the rest (104 genes) had no reported interactions.
Format: PDF Size: 308KB Download file
This file can be viewed with: Adobe Acrobat Reader
Additional file 3:
Cardiac septal defect associated OMIM records, genes and their immediate interactants (based on protein-protein interactions).
Format: PDF Size: 391KB Download file
This file can be viewed with: Adobe Acrobat Reader
Additional file 4:
Prioritized candidate genes for cardiac septal defects using PPIN- and functional annotation- based methods.
Format: XLS Size: 312KB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional file 5:
Prioritized candidate genes for cardiac septal defects using three PPIN-based methods and two functional annotation- based methods (ToppGene and ENDEAVOUR).
Format: XLS Size: 815KB Download file
This file can be viewed with: Microsoft Excel Viewer
Additional file 6:
Annotation and PPIN coverage of the human genes.
Format: XLS Size: 4.1MB Download file
This file can be viewed with: Microsoft Excel Viewer