Enio Gjerga

CAPRINI-M curates cardiac protein interactions using AI, integrating literature and structural data to improve PPI resource quality and performance.

The paper shows that genomic G quadruplexes regulate mRNA splicing by recruiting RNA-binding proteins, with implications for cardiac function.

The paper uses large language models to extract molecular interaction networks from scientific texts, achieving high precision and recall in protein-protein and gene regulatory network relations.

The paper presents TACOMA, a web tool integrating transcriptomics and proteomics data from a TAC-induced heart failure model, revealing molecular mechanisms of cardiac remodelling and failure.

Magnetique provides an interactive web tool to explore transcriptome signatures of heart failure using RNA-seq data from cardiomyopathy patients and donors.

This study applies adaptive sampling to direct RNA sequencing, showing efficient depletion of mitochondrial transcripts in human and mouse samples.

The paper uses network modeling to analyze how TP53 mutations affect gene regulation across cancer types and samples.

COSMOS integrates multi-omics data with prior knowledge to generate mechanistic hypotheses about biological processes in renal cell carcinoma.

The paper introduces updates to CellNOpt, a tool for building logic models from perturbation data and prior knowledge networks, including new methods and an interactive interface.

CARNIVAL identifies upstream causal processes from gene expression data by integrating prior knowledge, improving accuracy over existing tools in IgA nephropathy analysis.