Networks-based gene prioritization leverages previous work* of our collaborator Dr. Börnigen-Nitsch.
The algorithms are modified to accommodate variety of weighted data types to be used for gene prioritization (e.g. ranked gene to phenotype associations, weighted canonical pathways data). Various classes of information from our integrated knowledge-base are used for this networks-based gene prioritization.
*[Reference]: Nitsch D, Gonçalves JP, Ojeda F, de Moor B, Moreau Y (2010) Candidate gene prioritization by network analysis of differential expression using machine learning approaches. BMC Bioinformatics 11: 460