Yuval Itan

The paper establishes a global consortium to discover rare genetic associations by integrating data from multiple biobanks, identifying 514 gene-trait associations, many detectable only through cross-ancestry meta-analysis.

Adipocyte-specific deletion of Prdm16 ablates beige fat identity, derepresses the secreted enzyme Qsox1, and induces vascular fibrosis, angiotensin II hyperreactivity, and elevated blood pressure in mice.

This study identifies a proteomic signature in humans following acute cold exposure that correlates with cardioprotective and anti-aging effects.

This paper identifies a founder mutation in G6PC3 causing congenital neutropenia and shows it leads to loss of protein function and altered glycolysis.

LoGoFunc predicts pathogenic gain- and loss-of-function variants using ensemble learning with diverse biological features, outperforming existing tools.

The paper compiles 820 host genetic variants associated with COVID-19 susceptibility, develops a machine learning classifier to predict severity variants, and creates a web-based resource for exploring these variants.

The paper identifies gene- and protein-level features distinguishing gain-of-function and loss-of-function mutations using NLP and machine learning on a new database of pathogenic mutations.

The paper identifies 7 novel IBD-causing genes in Ashkenazi Jewish IBD patients using exome sequencing and analyzes their overlap with early-onset IBD and other diseases.

SeqTailor extracts DNA or protein sequences from VCF files for genetic variant analysis, providing a user-friendly webserver to support sequence-based predictions.

This study compares whole-genome sequencing (WGS) and whole-exome sequencing (WES) in six individuals, finding WGS more effective at detecting coding variants, particularly SNVs, with fewer false positives.