Chris Whelan
About Chris Whelan
Chris Whelan is a Senior Computational Biologist at the Broad Institute in Cambridge, Massachusetts, where he has worked since 2014. He specializes in developing computational methods for genetic analysis and leads a team focused on structural variation and prenatal clinical genetics.
Work at Broad Institute
Chris Whelan has served as a Senior Computational Biologist at the Broad Institute since 2014. In this role, he provides technical leadership to the Structural Variation Team, which consists of computational biologists and engineers. Whelan contributes to various research projects at the Stanley Center for Psychiatric Research, focusing on the understanding of complex structural variations and their links to disease risk. He leads efforts in developing and analyzing computational methods for processing maternal cell-free DNA sequencing data, which is essential for prenatal clinical genetics.
Education and Expertise
Chris Whelan earned a Bachelor of Arts in Computer Science from Harvard University, where he studied from 1993 to 1997. He furthered his education at Oregon Health & Science University, obtaining a PhD in Computer Science between 2008 and 2014. His academic background provides a strong foundation for his work in computational biology, particularly in the development of algorithms and pipelines for structural variation detection.
Background and Previous Experience
Before joining the Broad Institute, Chris Whelan held several positions that contributed to his expertise in computational biology and software engineering. He worked as a Principal Consultant at Avicon from 1999 to 2001 and served as a Senior Consultant at C-bridge Internet Solutions from 1997 to 1999. Whelan also had roles as a Senior Software Engineer at ACS from 2003 to 2006 and at Yesmail from 2006 to 2012. Additionally, he was a Doctoral Student at Oregon Health & Science University from 2008 to 2014, where he focused on advanced research in computer science.
Research Contributions
At the Broad Institute, Chris Whelan plays a significant role in advancing research in genetics. He focuses on developing algorithms and pipelines for detecting structural variations within the Genome Analysis Toolkit (GATK). His work involves applying machine learning techniques to enhance the accuracy of genetic variant calls, which are crucial for clinical diagnostics. Whelan's contributions are aimed at improving understanding of genetic factors related to health and disease.