Andrés López‐Cortés

NeoPhAR presents a deep learning model to predict phages for therapeutic use, aiming to simplify and democratize phage therapy for AMR infections.

This paper designs a multi-epitope vaccine against Mpox virus using immunoinformatics and computational epitope prediction, showing potential for robust immune responses and population coverage.

This study identifies essential genes in breast cancer using OncoOmics approaches, revealing 144 genes with 33% being cancer hallmarks and 14% significant across multiple methods.

The paper characterizes the ancestral origin of CFTR mutations in Ecuadorian patients, finding high Native American ancestry with exceptions in three individuals with European ancestry.

The paper develops an artificial neural network model to predict breast cancer-related proteins, achieving high accuracy and identifying top-ranked proteins in three categories.

The paper develops a machine learning model to predict druggable proteins, achieving high accuracy, and identifies potential targets in cancer and RNA-binding proteins.

This paper reviews pharmacogenomics biomarkers and genomic alterations in colorectal cancer to improve precision medicine strategies, with a focus on Latin America.

The paper performs genomic, ancestral, and networking analysis on a high-altitude Ecuadorian CIPA patient, identifying NTRK1 mutations and associated variants.