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A scalable and flexible framework for analyzing large-scale genomic data

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Date: Tuesday, 12th January, 2021
Time: 09 am - 10 am Pacific Time
(US and Canada)
Location: Online

A scalable and flexible framework for analyzing large-scale genomic data

Next generation sequencing (NGS) has fundamentally transformed basic and applied life sciences research providing new insights into our understanding of health and disease. Nowadays, a typical NGS-based experiment can produce vast amounts of data of different types and complexities that need to be managed, integrated and analyzed for meaningful interpretation. Bioinformatics is an interdisciplinary field that combines computer science, statistics and life sciences and is a crucial component of genomics data analysis. We have leveraged the technological advancements in the field of computational biology and genomics to develop a comprehensive suite of bioinformatics pipelines for NGS data analysis. We use state-of-the-art bioinformatics algorithms and pipelines to deliver high-quality and publication-ready figures and analysis reports for our projects.

In this webinar, Dr. Kushal Suryamohan will provide an overview of our framework for scalable and reproducible analysis and visualization of a broad range of genomics data types including whole genome sequencing, transcriptomics, single cell genomics, immune profiling and genome assembly and annotation.


Speaker Profile

Kushal Suryamohan

Bioinformatics Scientist, MedGenome

Kushal Suryamohan is a Bioinformatics Scientist at MedGenome, Inc, USA and leads the commercial bioinformatics services team. He oversees the optimization as well as development of pipelines for NGS data analysis. Previously, he worked at Genentech where he focused on analyzing long read, optical map sequencing and chromatin capture technology data to generate high quality de novo genome assemblies. He was also actively involved in applying high throughput NGS-based functional genomic screens of oncogenes to characterize oncogene function in cancer. His work has led to multiple publications in high-impact journals including Nature, Nature Genetics and Developmental Biology. He holds a PhD in Biochemistry and a Masters degree in Computer Science the University at Buffalo, State University of New York.

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