Dr. Arif Harmanci arrived at SBMI in the fall of 2017. Harmanci received his Master’s and PhD degrees in Electrical Engineering from University of Rochester, NY. His PhD thesis addresses the modeling of homologous structures of non-coding RNA sequences. He has developed several state of the art structure prediction methods that are being used today.
For his postdoctoral studies he moved to Yale University. His postdoctoral studies at Yale focused on genomics and analysis of DNA sequencing data. He has taken a particular interest in analysis of functional genomics data that probe complex regulatory processes in human genome. At Yale, he has been involved as a key member in several consortium projects such as ENCODE, modENCODE, and 1000 Genomes.
His research interests cover a large spectrum of topics in computational biology including functional genomics data analysis, non-coding variation, genotype-phenotype associations, cancer genomics, biological networks, and development of novel machine learning methods for biomedical data analysis. He is also working extensively on implications of large genomic data on personal privacy. In this arena, he is developing computational methods that enhance privacy considerations around analysis and sharing genomic data. Dr. Harmanci’s research reveals ways to understand how an individual’s privacy can be protected when their genome is being shared and analyzed in clinical and other settings. His studies has yielded publications in high impact journals like Nature and Science and his projects have been highlighted in the media and in professional journals.