GUILDify v2.0: A Tool to Identify Molecular Networks Underlying Human Diseases, Their Comorbidities and Their Druggable Targets

Joaquim Aguirre-Plans, Janet Piñero, Ferran Sanz, Laura I. Furlong, Narcis Fernandez-Fuentes, Baldo Oliva, Emre Guney

Research output: Contribution to journalArticlepeer-review

26 Citations (SciVal)
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Abstract

The genetic basis of complex diseases involves alterations on multiple genes. Unraveling the interplay between these genetic factors is key to the discovery of new biomarkers and treatments. In 2014, we introduced GUILDify, a web server that searches for genes associated to diseases, finds novel disease genes applying various network-based prioritization algorithms and proposes candidate drugs. Here, we present GUILDify v2.0, a major update and improvement of the original method, where we have included protein interaction data for seven species and 22 human tissues and incorporated the disease–gene associations from DisGeNET. To infer potential disease relationships associated with multi-morbidities, we introduced a novel feature for estimating the genetic and functional overlap of two diseases using the top-ranking genes and the associated enrichment of biological functions and pathways (as defined by GO and Reactome). The analysis of this overlap helps to identify the mechanistic role of genes and protein–protein interactions in comorbidities. Finally, we provided an R package, guildifyR, to facilitate programmatic access to GUILDify v2.0 (http://sbi.upf.edu/guildify2)
Original languageEnglish
Pages (from-to)2477-2484
Number of pages8
JournalJournal of Molecular Biology
Volume431
Issue number13
Early online date07 Mar 2019
DOIs
Publication statusPublished - 14 Jun 2019

Keywords

  • traget prioritization
  • systems medicine
  • network analysis
  • disease comorbidity
  • drub repurposing
  • drug repurposing
  • target prioritization
  • Genetic Predisposition to Disease
  • Comorbidity
  • Humans
  • Computational Biology/methods
  • Drug Design
  • Gene Regulatory Networks/drug effects
  • Software

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