Motivation: Over the past decade, network-based approaches have proven useful in identifying disease modules within the human interactome, often providing insights into key mechanisms and guiding the quest for therapeutic targets. This is all the more important, since experimental investigation of potential gene candidates is an expensive task, thus not always a feasible option. On the other hand, many sources of biological information exist beyond the interactome and an important research direction is the design of effective techniques for their integration.Results: In this work, we introduce the Biological Random Walks (BRW) approach for disease gene prioritization in the human interactome. The proposed framework leverages multiple biological sources within an integrated framework. We perform an extensive, comparative study of BRW's performance against well-established baselines.
2022, BIOINFORMATICS, Pages 4145-4152 (volume: 38)
Biological Random Walks: multi-omics integration for disease gene prioritization (01a Articolo in rivista)
Gentili Michele, Martini Leonardo, Sponziello Marialuisa, Becchetti Luca
Gruppo di ricerca: Algorithms and Data Science