Seminar: Computational Methods for Detecting Structural Variants in the Next Generation Sequencing Data and Its Applications” Dr. Emre Karakoç (Medipol University), EA-409, 3:40PM December 21 (EN)

S E M I N A R: “Computational Methods for Detecting Structural Variants in the Next Generation Sequencing data and its applications” by Asst. Prof. Dr. Emre Karakoç, Medipol University

Despite the ease at which genome sequence data can be generated, most studies and standard computational pipelines to date, focus on the detection of single nucleotide variants and small insertions and deletions(indels). The main reason for this situation is that there are no robust methods for detecting larger indels and structural variations. Here I present novel computational methods for detecting these under estimated variants. In addition I developed computational system biology models using this more complete view of the variant landscape, to detect molecular pathways associated with complex diseases and to understand their etiology. Genomic variants especially structural variants, also contribute significantly to the adaptive evolution and introgression across closely related species. I applied computational and statistical methods to shed light on to human evolution and bacterial resistance.

Bio: Emre Karakoc is currently an Assistant Professor at the Department of Computer Engineering at Istanbul Medipol University since March 2016. He graduated from Bilkent University Dept. of Computer Engineering in 2002, and received his Ph.D. in Computer Science from Simon Fraser University in 2007. During his Ph.D. he worked on the RNA secondary structure prediction, RNA-RNA interaction prediction and QSAR models for clustering small chemical molecules. He then joined the Department of Genome Sciences of the University of Washington as a postdoctoral fellow. He worked on identification of small insertions and deletions from next generation sequencing data, computational prediction of human variation and system biology applications (protein-protein interactions) of these variants in complex diseases such as autism. He then joined the Max Planck Institute for Evolutionary Biology as a postdoctoral researcher where he worked on population genetics, specifically developing computational methods for identification of admixture and adaptive introgression. Since then he is applying combinatorics algorithms on a wide range of biological problems.

DATE: 21 December 2017, Thursday @ 15:40