Michal Hledík

The paper introduces the quantitative omnigenic model (QOM) to improve GWAS interpretability by integrating regulatory network knowledge, showing it can predict gene expression with fewer parameters and extract causal effect chains.

This paper unifies normative theories and statistical inference in a Bayesian framework for biological systems analysis, demonstrating its application to neural data.