Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond.

ABSTRACT:

Background

Biological networks have proven invaluable ability for representing biological knowledge. Multilayer networks, which gather different types of nodes and edges in multiplex, heterogeneous and bipartite networks, provide a natural way to integrate diverse and multi-scale data sources into a common framework. Recently, we developed MultiXrank, a Random Walk with Restart algorithm able to explore such multilayer networks. MultiXrank outputs scores reflecting the proximity between an initial set of seed node(s) and all the other nodes in the multilayer network. We illustrate here the versatility of bioinformatics tasks that can be performed using MultiXrank.

Results

We first show that MultiXrank can be used to prioritise genes and drugs of interest by exploring multila

SUBMITTER: Baptista A 

PROVIDER: S-EPMC10865648 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature