Elodie Ghedin

This paper introduces NbForge, a nanobody folding model that improves prediction of HCDR3 blueprint and disulphide bonds, achieving accuracy comparable to large predictors with faster speed.

SurfDiff predicts epitope selectivity and cross-reactivity by analyzing protein surface features, outperforming existing metrics in binder and immunogen design.

This study characterizes the microbiome of Total Suspended Particles (TSP) and finds correlations between indoor TSP and the upper respiratory microbiome of office workers.

This study shows that CD4+ and CD8+ T cells are necessary to prevent SARS-CoV-2 persistence in the nasal compartment but not in the lungs.

The paper analyzes baseline multi-omic data from influenza vaccine recipients to identify pre-immune states predictive of vaccination responses.

The paper demonstrates miniature spatial transcriptomics to study gene expression patterns in filarial worms and their Wolbachia endosymbionts, revealing spatial gene localization and interactions.

This study uses a network-based approach to analyze sex differences in immune responses to influenza virus infection in ferrets, identifying sex-biased gene expression and pathways.

iGenomics provides a mobile application for DNA sequence analysis on iOS devices, offering alignment, variant calling, and visualization comparable to desktop tools.

The paper models the metabolic interactions between a parasitic worm and its bacterial endosymbiont to identify potential drug targets.

The paper develops a motif prediction pipeline to identify regulatory motifs in Brugia malayi, focusing on those involved in the L3-L4 molt stage.

This study uses high-resolution proteomics to identify 26 differentially expressed proteins that can predict Zika virus infection with 72% accuracy using a machine learning model.