Avetis / Generating, Accessing and Processing of Biomedical Data

Generating, Accessing and Processing of Biomedical Data

Davit Sargsyan

Davit Sargsyan is the Associate Director in the Translational Medicine and Early Development Statistics group, Janssen PRD, J&J. He is a Graduate Student at Dr. Kong’s Lab, E. Mario School of Pharmacy, Rutgers, and a researcher at the Cardiovascular Institute of New Jersey, RWJ Medical School, Rutgers. Davit studied economic statistics at the Armenian State University of Economics before moving to the US to continue his education. He earned his master’s degree in 2011 from the Statistics department at Rutgers University and has been working at Janssen Pharmaceutical Research and Development since 2011. Davit is supporting Drug Discovery teams including immunology, bioassay development, and cardiovascular and metabolism. His main area of interest is genomics and epigenomics data analysis and visualization including microarray, RNA, and DNA sequencing data, as well as investigating the role of the microbiome in modulating the human immune system, especially in patients with inflammatory bowel diseases such as ulcerative colitis and Chron’s disease. Davit is conducting epidemiological research at Robert Woods Johnson Medical School and has co-authored multiple publications related to cardiovascular disease patients’ long-term outcomes.

The full list of his publications can be found on his Google Scholar page.

Venue: Video Conference via Zoom
Time: 19:00-21:00 Yerevan time
Objectives:

In this talk, we will provide an overview of drug development and the design of experiments to better understand the biomedical data generation and collection process. We will cover data formatting and accessing. Several data models will be discussed and compared. An example of a large coded dataset will be provided, and ways to access and manipulate it in the R programming language will be given.In this talk, we will provide an overview of drug development and the design of experiments to better understand the biomedical data generation and collection process. We will cover data formatting and accessing. Several data models will be discussed and compared. An example of a large coded dataset will be provided, and ways to access and manipulate it in the R programming language will be given.

Presentation Slides: Presentation slides: Generating, Accessing and Processing of Biomedical Data
Video: