Supplementary Information and Source Code

(Last update 08/18/2009)

Matlab [Matlab Source code]

Source code: MINProp [Readme]

Disclaimer

This software is free only for non-commercial use. It must not be distributed without prior permission of the author. The author is not responsible for implications from use of this software.

Experiments

Datasets

1. Disease Phenotype Similarity Network: [Matlab data]

: Each node indicates disease phenotype, each edge is weighted by disease similarity obtained by text mining.

There are 5,080 disease phenotypes in the phenotype network.

The first column indicates OMIM number of disease phenotype.

Original data is from the following reference:

[Marc A. van Driel, Jorn Bruggeman, Gert Vriend, Han G. Brunner, and Jack A.M. Leunissen. "A text-mining analysis of the human phenome." (2006), European Journal of Human Genetics,14, 535-542. PMID: 16493445]

2. Protein-Protein Interaction: [Matlab data]

: Each node indicates protein, and each edge indicates protein interactions.

There are 8,919 proteins.

Note that we remove self-interactions (i.e. protein A interacts protein A itself) in our experiments.

Original data is from the following reference:

[Wu X, Jiang R, Zhang MQ, Li S (2008) Network-based global inference of human disease genes. Molecular Systems Biology, 4:189]

3. Disease Phenotype-Gene Network (in May 2007): [Matlab data]

: Each row represents disease phenotype, and column represents genes.

Binary values in data indicate disease-gene associations. (i.e. if gene1 is causative gene for disease phenotype 1, matrix(1,1) indicates 1)

Original data is from the following reference:

[Wu X, Jiang R, Zhang MQ, Li S (2008) Network-based global inference of human disease genes. Molecular Systems Biology, 4:189]

Results

Leave one out cross-validation results

1. Uncovering associations with known disease genes: [Link]

2. Discovering associations with new disease susceptibility genes: [Link]