Laura Ines Furlong

DISGENET: Accelerating Data-Driven Discovery in Disease Genomics and Therapeutic Development

DISGENET integrates genotype-phenotype data to support precision medicine and drug development through comprehensive, up-to-date associations and tools.

A versatile and interoperable computational framework for the analysis and modeling of COVID-19 disease mechanisms

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

Behavioural and transcriptomic characterization of the comorbidity between Alzheimer s disease and Major Depression

This study identifies shared transcriptomic changes between Alzheimer's disease and Major Depression in mice, suggesting Major Depression may be an early manifestation of Alzheimer's.

Capturing variation impact on molecular interactions: the IMEx Consortium mutations data set

The paper presents a dataset of 28,000 annotations describing how amino acid mutations affect protein interactions, available through the IntAct website.

Targeting comorbid diseases via network endopharmacology

This study introduces PxEA, a network-based method to identify drugs targeting common pathways across diseases, demonstrating drug repurposing opportunities for autoimmune disorders and comorbid conditions like type 2 diabetes and Alzheimer's disease.

Genetic and real-world clinical data, combined with empirical validation, nominate JAK-STAT signalling as a target for Alzheimer’s Disease therapeutic development

The paper combines GWAS, clinical data, and experimental models to identify JAK-STAT pathway dysregulation as a potential therapeutic target for Alzheimer’s disease.