Dr. Ahmet Rifaioglu will give a seminar on “Analysis of single-cell RNA sequencing data” on 13 December at 13:40. The abstract of the talk and a short bio is shared below.

Bio:
Dr. Rifaioglu received his Ph.D. from the METU Computer Engineering department in 2020. In his Ph.D., he mainly worked on developing deep learning methods for drug discovery in the context of a project called "CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations". He spent one year of his Ph.D. at EMBL-European Bioinformatics Institute as a pre-doctoral visiting researcher in the context of the CROssBAR project. After working as an assistant professor at Iskenderun Technical University for a short time, he joined Heidelberg University as a post-doctoral researcher. His research now focuses on developing computational methods for single-cell genomics in cancer.

Abstract:
With the advance of single-cell RNA sequencing technologies, we can now get whole transcriptome information for a large number of cells. These technologies enabled us to identify cell types, understand cell-cell communication and their microenvironment in general. Computational methods are required to understand and process the high-throughput single-cell transcriptomics data. In this presentation, I will talk about the standard practices and challenges in the computational analysis of single-cell RNA sequence datasets.