Ben Weisburd
About Ben Weisburd
Ben Weisburd is a computational biologist with extensive experience in genomic data analysis. He currently works at the Broad Institute, where he manages various genomic pipelines and has contributed to significant projects in the field.
Work at Broad Institute
Ben Weisburd has been employed at the Broad Institute as a Computational Biologist since 2014. He works in the Daniel MacArthur Lab, where he manages short tandem repeat (STR), SMN, and RNA-seq pipelines for the Broad Center for Mendelian Genomics. His responsibilities include overseeing the development of tools and resources that enhance genomic data analysis. Notably, he led the release of the first short tandem repeat (STR) callset from gnomAD and contributed to the updated gnomAD browser, improving its functionality for researchers in the field.
Previous Experience in Genomic Data Analysis
Prior to his current role, Ben Weisburd worked as a Contractor for Novartis (NIBR) from 2012 to 2014, focusing on next-generation sequencing (NGS) data analysis. He also served as a Software Engineer at the Broad Institute for six months in 2010. His early career included an internship at Brandeis University in the Complex Fluids Lab from 2002 to 2004, and a position as a Software Engineer at MIT Lincoln Laboratory from 2006 to 2009.
Education and Expertise
Ben Weisburd earned a Bachelor of Science (BS) degree in Computer Science from Brandeis University, where he studied from 2001 to 2005. His educational background provides a strong foundation for his work in computational biology and genomic data analysis. His expertise includes the development of web-based tools for analyzing rare disease datasets, such as seqr, which is hosted on GitHub.
Contributions to Genomic Databases
Throughout his career, Ben Weisburd has made significant contributions to genomic databases. He led the development of the first short tandem repeat (STR) callset from gnomAD, which is a critical resource for genomic research. Additionally, he has played a key role in enhancing the gnomAD browser, making it more functional for users engaged in genomic analysis.