Disease candidate gene identification and prioritization using protein interaction networks

doi:10.1186/1471-2105-10-73

BMC Bioinformatics

Volume 10

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Research article

Disease candidate gene identification and prioritization using protein interaction networks

Jing Chen¹^,2 , Bruce J Aronow¹^,2^,3 and Anil G Jegga¹^,3

¹Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA

²Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH, USA

³Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

author email corresponding author email

BMC Bioinformatics 2009, 10:73doi:10.1186/1471-2105-10-73


Published:	27 February 2009

Additional files

Additional file 1:

Venn diagrams of unique genes and interactions from the three (BIND, BioGRID, and HPRD) PPIN data source.

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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

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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

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Additional file 4:

Prioritized candidate genes for cardiac septal defects using PPIN- and functional annotation- based methods.

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Additional file 5:

Prioritized candidate genes for cardiac septal defects using three PPIN-based methods and two functional annotation- based methods (ToppGene and ENDEAVOUR).

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Additional file 6:

Annotation and PPIN coverage of the human genes.

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