Abdülkadir Elmas

The paper analyzes how mutations affect mRNA and protein expression in 953 cancer cases across six types, finding that 47.2% of somatic expression quantitative trait loci (seQTLs) impact protein levels, with some mutations showing disproportionate effects.

The paper identifies Master Protein abundance Regulators (MaPRs) across ten cancer types using a computational pipeline, finding they mediate up to 79% of post-transcriptional regulatory networks and predict tumor proteomic subtypes more accurately.

The paper identifies expression-driven genetic dependency targets for precision oncology using a Bayesian approach, revealing new druggable genes and validating their therapeutic potential.

This study uses Mendelian Randomization to identify causal relationships between circulating biomarkers and diseases, finding novel associations between glucose and cystatin C with bipolar disorder.

The paper introduces HotPho, a tool that identifies 3D co-clustering of phosphosites and cancer mutations on protein structures, revealing 474 hybrid clusters with potential functional significance.