Work

Disease Understanding and Visualization of Drug Repurposing Hypotheses

Year: 2025

Type: conference-paper

Abstract: The increasing availability of biomedical data has opened new opportunities to rethink how diseases are modeled and how drug repurposing hypotheses can be systematically generated. In this context, we present a web-based platform that (i) provides access to previously integrated heterogeneous biomedical data and (ii) enables interactive visualization of disease understanding relationships, as well as of drug repurposing hypotheses. The platform constructs multilayer disease networks, visualizes disease relationships, and implements six complementary computational repurposing methods, including more naive methods, network-based analysis, and artificial intelligence-based approaches. It also provides the web services needed to access the whole set of data. This paper describes the underlying data sources and methodologies and demonstrates its capabilities through a representative visualization case.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17355426

Authors: Prieto Santamaría, Lucía, Otero Carrasco, Belén, Álvarez Pérez, Andrea, David, Juste Urraca, Rodríguez González, Alejandro

Institution: Universidad Politécnica de Madrid

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Ministerio de Ciencia, Innovación y Universidades, Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España