Predicting new gene-disease associations by a disease-aware evaluation of heterogeneous molecular networks

Get paper here: de la Fuente et al., 2023

Cite us: de la Fuente L, Del Pozo-Valero M, Perea-Romero I, Blanco-Kelly F, Fernández-Caballero L, Cortón M, Ayuso C, Mínguez P. Prioritization of New Candidate Genes for Rare Genetic Diseases by a Disease-Aware Evaluation of Heterogeneous Molecular Networks. International Journal of Molecular Sciences. 2023; 24(2):1661. 

A compilation of heterogeneous networks representing  13 different knowledge categories covering different aspects of cell regulation and knowledge generation

Disease-specific evaluation of every knowledge category

Network-based algorithm using a random-walk with restart propagation model (RWWR) that 

systematically evaluates and compares KCs ability to recover genes on a given list associated to the studied phenotype/disease 

Disease-aware integration of evidence sources

How to run?

2. Download heterogeneous knowledge networks 

3. Prepare your list of phenotype-related genes

4. Run GLOWgenes and find your candidates!!