Lionel Spinelli

The paper uses single-cell RNA sequencing to analyze immune cell interactions in asymptomatic and symptomatic malaria patients, finding reduced monocyte-T cell interactions and increased inflammation in symptomatic cases.

SciGeneX detects gene modules in single-cell and spatial transcriptomics data to reveal cell populations, outperforming existing methods and uncovering rare cell types in human thymus data.

mimicINT identifies microbe-host protein interactions by detecting molecular mimicry elements, showing effectiveness in analyzing bacterial and viral interactions with human proteins.

This study identifies and characterizes the functional roles of microproteins (sPEPs) in three human tissues, revealing two distinct functional groups and their regulatory roles.

This study identifies two distinct pathogenic pathways in Chronic Chagas Cardiomyopathy through multi-omics integration, involving IRF4 and TLR signaling, with B cell-related genes and shared B cell receptor features.

The paper constructs an RNAP2 ChIP-seq atlas and integrates it with RNA-seq data to identify intergenic transcription as a biomarker in normal and cancer tissues.

ShIVA provides a user-friendly interface for biologists to analyze single-cell RNA-seq and CITE-seq data using Seurat v4, enabling reproducible analysis and visualization.

The paper identifies genetic networks and regulatory elements associated with cardiac performance variation in Drosophila and finds conserved genetic architecture between flies and humans.

The paper introduces epiMEIF, a method for detecting high-order epistatic interactions in GWAS data, showing its effectiveness through simulations and an application to Drosophila cardiac traits.

MetamORF compiles and normalizes unique short ORFs from human and mouse genomes using experimental and computational methods, enabling new analyses of sORF functions.

The paper introduces a multicolor BiFC library for studying protein-protein interactions in live Drosophila using Hox proteins as a case study.

The paper identifies candidate virulence proteins of Fusobacterium nucleatum that interact with human proteins involved in inflammatory bowel disease and colorectal cancer.