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Aspects of High Throughput Molecular Data Analysis

About This Webinar

The molecular information acquisition is gaining strong presence in every aspect of life. Much of this stems from the decreasing cost of DNA sequencing and computational power. Coupled with the data, computational methods are generating waves of interesting results. Interestingly, we are far from making sense of the extremely complicated molecular data. The more data we generate, the more we realize the complexity of the cellular information processing. These developments bring so many exciting opportunities and challenges. In this presentation, I will review different aspects of how triage of genomics, transcriptomics, epigenetics is changing the way we understand how molecular health translates to individual health. I will also review some of the future challenges related to high throughput data acquisition and data analysis.

Who can view: Everyone
Webinar Price: Free
Webinar ID: 0273291096fc
Featured Presenters
Webinar hosting presenter ISCB SC RSG Turkey
ISCB RSG Turkey Crew
Webinar hosting presenter
Dr. Arif Harmanci arrive 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.
Hosted By
BioInfoNet webinar platform hosts Aspects of High Throughput Molecular Data Analysis
BioinfoNet is an online community for online bioinformatics meetings initiated by ISCB SC RSG Turkey. This meetings include free webinars and paper clubs.
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