Kemal Turhan

This study evaluates protein representation learning methods across three tasks: semantic similarity, function prediction, and drug target classification, highlighting their strengths and limitations.

The paper develops a personalized tumor growth model using multiscale simulation and Bayesian methods, showing promising predictions with low error margins on A549 cell line data.