Çiğdem Sevim Bayrak

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

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.