Detection of SUMOylation sites that emerge through mutations in cancer

2021-2022 Summer
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 

In our group we had developed a tool DeepKinZero, a deep learning model for identification of possible phosphorylated sits by understudied kinases. The project will involve using this tool to discover somatic mutations that can lead to change in the phosphorylation state. The students will work with the cancer genome atlas patient data and integrate it with the DeepKinZero predictions. Good programming skills are required.

Related Areas of Project: 
Computer Science and Engineering
Molecular Biology, Genetics and Bioengineering
Electronics Engineering

About Project Supervisors

Öznur Taştan
Faculty of Engineering and Natural Science