Janet Piñero

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

The paper develops a regulatory network model of nucleus pulposus cells to simulate ECM regulation in intervertebral discs, showing how perturbations affect catabolic and anabolic processes.

The paper develops two novel knowledge graph embedding algorithms, DLemb and BioKG2Vec, which outperform existing methods in predicting gene-disease associations, particularly for diseases with limited information.

Genopyc is a Python library for analyzing complex diseases' genetic basis, enabling integration and visualization of genomic data to uncover dysregulated pathways.

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

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.

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

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.