Mike Lawrence
About Mike Lawrence
Mike Lawrence is a Group Leader in Computational Biology at the Broad Institute, where he has worked since 2014. He specializes in analyzing cancer genomics data and collaborates with clinical teams to enhance personalized medicine approaches for cancer treatment.
Work at Broad Institute
Mike Lawrence has served as Group Leader in Computational Biology at the Broad Institute since 2014. In this role, he leads a team focused on analyzing large cancer sequencing datasets. His work involves collaboration with clinical teams to investigate mutational heterogeneity, which is crucial for understanding cancer progression and treatment responses. Prior to his current position, he worked as a Computational Biologist at the Broad Institute from 2008 to 2014, where he contributed to various projects related to cancer genomics.
Education and Expertise
Mike Lawrence earned his Ph.D. in Biochemistry from the Massachusetts Institute of Technology, where he studied from 1998 to 2005. He also holds a Bachelor of Arts degree in Biochemistry and Linguistics from Brandeis University, completed in 1998. His educational background provides a strong foundation for his expertise in computational biology, particularly in cancer genomics and personalized medicine.
Background in Cancer Genomics
Lawrence's research focuses on analyzing cancer genomics data using computational methods. His work addresses key areas such as carcinogenesis, treatment response, resistance development, and metastasis. He has developed the MutSig software suite, which is used for the statistical identification of significantly mutated genes, contributing to the understanding of cancer biology.
Current Role at Harvard Medical School
Since 2016, Mike Lawrence has been an Assistant Professor at Harvard Medical School and Massachusetts General Hospital. His role involves furthering research in cancer genomics and collaborating with clinical teams to enhance the understanding of cancer treatment and prevention. His position at this prestigious institution allows him to integrate his computational biology expertise with clinical applications.
Research Contributions
Lawrence's research includes extracting novel insights from mutational strand asymmetries in cancer genomes. He emphasizes genomics-informed personalized medicine, aiming to improve cancer prevention, diagnosis, prognosis, and treatment strategies. His contributions are significant in the field of computational biology and cancer research.