Seminar: Cancer Bioinformatics

Abstract: Completion of the human genome project and recent developments in high throughput molecular technologies have enabled the detailed genomic, epigenomic and transcriptomic profiling of biological specimens in unprecedented detail for exponentially declining costs. This situation has resulted in the generation of a vast amount of data, which has great potential to improve human health outcomes substantially. Analysis of this complex, noisy, and contextdependent data is challenging; hence Bioinformatics or Computational Biology has emerged as a novel field for efficient utilization of this valuable data. This presentation will include the basic concepts in cancer bioinformatics and highlights from Dr. Baysan’s recent research activities. After providing a brief molecular biology background; current technologies, trends and major challenges in cancer bioinformatics will be presented. These will be followed with Dr. Baysan’s recent findings in Cancer Subtyping, Evalua tion of Experimental Cancer Models and Intra-Tumor Heterogeneity.

Speaker: After obtaining his B.S. from Bilkent University in Computer Science in 2003, Dr. Mehmet Baysan completed his M.S. and Ph.D. degrees in Computer Science at The University of Texas at Dallas in 2005 and 2008, respectively. After his Ph.D., he worked for a year at the Management Department of University of Toronto as a post-doctoral fellow. During graduate school and his first post-doctoral fellowship, the focus of his research was developing optimal solutions for problems in new application areas, based on emerging technologies. With this aim, Dr. Baysan studied major problem solving techniques in algorithms, graph theory and combinatorial optimization. In his research projects, he applied these classical problem-solving techniques to problems that are critical for major applications in wireless networks and supply-chain systems. In 2010, Dr. Baysan switched his research focus to the area of computational biology as a post-doctoral fellow at the Neuro-Oncology Branch of the National Cancer Institute (NCI) of the NIH, USA. After his fellowship, he moved to NYU Cancer Institute and later to Weill Cornell Medical College as an Associate Research Scientist in 2013 and 2015, respectively. Since 2010, his research has centered on improving our understanding of cancer genomics with the use of computational tools. Dr. Baysan is especially interested in the integration of multiple data sets with different data types for efficient interpretation of available data to aid cancer diagnosis and treatment.