Work

Robustness in Protein-Protein Interaction Networks: A Link Prediction Approach

Year: 2025

Type: conference-paper

Abstract: Protein-protein interaction networks (PPINs) are indispensable in exploring complex biological systems, facilitating advancements in fields like drug discovery, protein function annotation, and disease mechanism elucidation.So far, predicting the dynamical properties of biochemical pathways has relied on costly numerical simulations.In this paper, we propose exploiting the topological information in PPINs to restate the problem of predicting pathway robustness as a link prediction task.Our experiments show that the PPIN topology can supply information on inter-pathway relationships, significantly improving predictions of the graph-agnostic baseline relying only on protein sequence embeddings.

Source: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN)

DOI: 10.14428/esann/2025.es2025-153

Authors: Alessandro Dipalma, Domenico Tortorella, Alessio Micheli

Institution: University of Pisa

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: bronze

Funder: European Commission

Awards: G1115267702, G4508289328, G5376833654, G8409961469