CS Seminar: “Identification of protein-protein interaction bridges for multiple sclerosis”, Gözde Yazıcı, 11:00AM December 23 (EN)

M.S. THESIS DEFENSE PRESENTATION Title: Identification of protein-protein interaction bridges for multiple sclerosis

Gözde Yazıcı, M.Sc. Student in Computer Engineering
Advisor: Assoc. Prof. Dr. Can Alkan
Member: Prof. Dr. Uğur Doğrusöz
Assoc. Prof. Dr. Tunca Doğan (Hacettepe Uni.)

The Seminar will be on Friday, December 23, 2022, 11:00 am İstanbul

This is an online seminar. To request the event link, please send a message to department.

Identifying and prioritizing disease-related proteins is an important scientific problem to understand disease etiology. Network science has become an important discipline to prioritize such proteins. Multiple sclerosis (MS), an autoimmune disease which still cannot be cured, is characterized by a damaging process called demyelination. Demyelination is the destruction of myelin, a structure facilitating fast transmission of neuron impulses, and oligodendrocytes, the cells producing myelin, by immune cells. Identifying the proteins that have special features on the network formed by the proteins of oligodendrocyte and immune cells can reveal useful information about the disease, and help the relevant research improve. To this end, we investigated the most significant protein pairs for the intracellular and intercelluar protein networks that we define as bridges among the proteins providing the interaction between the two cells in demyelination using network analysis techniques and integer programming. We analyzed two protein networks formed by the oligodendrocyte and each type of two immune cells (i.e., macrophage and T-cell). We developed a model called BriFin that first evaluates the intracellular importance scores of the contact proteins using network analysis techniques, and then prioritizes contact protein pairs based on these scores and the intercellular interactions by integer programming. The reason we investigated these specialized hubs was that a problem related to these protein pairs might impose a bigger damage in the system due to their position in the protein network. As an indication about the performance of BriFin, we showed several proteins it detected as having the highest priority have already been associated with MS in the relevant literature. We further observed the mRNA expression levels of several proteins BriFin prioritized significantly decreased in a group of MS patients. We therefore here present a model, BriFin, which can be used for analyzing processes where interactions of two cell types play an important role.