Scientific Context of the Project

Cancer cells have different physiological and biological characteristics. Utilizing these characteristic differences, different technologies could be created for cancer diagnosis and therapeutic purposes. In this proposed project, a new image-based cytometer method will be developed for automated, rapid, and reliable characterization of cells in a microfluidic chip by investigating the morphological, size, deformation, density, and magnetic properties of cells without using any labels. This method will be used for high-efficient detection of rare cancer cells among blood cells for diagnosis and prognosis purposes, as well as enabling the analysis of cancer cell responses to the drugs at the single-cell level.

Related References:

1. PNAS, 2015, 112, E3667-E3668.

2. ACS Sensors, 2021, 6, 2191-2201.

3. SPIE BIOS, LBIS, 2021, 1165509.

Innovative Aspects of the Project 

Novel cytometers will be developed by harmonizing microfluidics technology and deep learning-based data analysis that will enable sensitive and label-free single cell analysis.

Research Environment and Infrastructure

Rapid prototyping tools, cleanroom facility, cell imaging facility, cell culture facility and well-equipped characterization and bioengineering centers (https://tam.iyte.edu.tr/en/homepage/)

Preferred Academic Background

Electrical and Electronics Engineering, Computer Engineering, Bio/biomedical Engineering, Molecular Biology and Genetics

Required GRE Score

GRE Quantitative 157.00