Senior Bioinformaticist
Sudeep Mehrotra graduated from University of Saskatchewan, Canada and holds an MS in the field of Bioinformatics and completed a BS (honors degree) with a major in Computer Science and minor in Mathematics from Trent University, Canada. As a researcher, he gained valuable experience at McGill University. In his academic and work span he has gained extensive experience in Proteomics, Genomics, Metagenomics and Software Engineering (at McGill University Genome Quebec Innovation Center and New York Genome Center).
Sudeep is an avid reader and a good book can keep him thoroughly engrossed. He believes in gathering knowledge, and application of it and perseverance towards the goal are critical elements of being successful.
In February 2017, Sudeep Mehrotra joined Dr. Pierce’s lab to work as a Senior Bioinformaticist at OGI where his focus is on data analysis and interpretation of various projects in OMIC’s (genomics, metagenomics and transcriptomics).
Contact Information:
sudeep_mehrotra@meei.harvard.edu
Bioinformaticist
Juerg Strabhaar has a MS in Physics from the University of Bern in Switzerland and
a PhD in Biochemistry from Clemson University, SC. He started his
bioinformatics career as a postdoc in the lab of Gary Stormo at the
University of Colorado at Boulder where he worked on sequence pattern
recognition algorithms. He then assumed a bioinformatics position with
Serono in Braintree and Rockland, MA, where he analyzed microarray
data, which were introduced at that time into molecular biology labs
to investigate genome-wide gene expression. He moved back to academia
as a research assistant professor at the University of Massachusetts
Medical School in Worcester, MA. There, together with a group of
computer scientists and bioinformaticians, he built a microarray
database, expanded it to include miRNA data and tools for downstream
analyses. Before joining OGI he was scientific staff in the
informatics group of FAS at Harvard where he developed expertise in
single cell RNAseq processing and analysis, proteomics data analysis
and developing a single cell proteomics pipeline.