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Michael S. Lawrence

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Michael Scott Lawrence
Other namesMike Lawrence
Alma materBrandeis University
Massachusetts Institute of Technology
Known forMutSig[1][2]
Scientific career
FieldsGenetics
InstitutionsMassachusetts General Hospital
Harvard Medical School
Broad Institute
ThesisRNA polymerase ribozymes (2005)
Doctoral advisorDavid Bartel

Michael Scott Lawrence is an American geneticist best known for his work on mutational signatures. Lawrence is an assistant professor of pathology at the Harvard Medical School, Assistant Geneticist at the Massachusetts General Hospital, and member of the Broad Institute.

Biography

Lawrence earned his B.A. degree in biochemistry from Brandeis University in 1998 and his Ph.D. degree in Biology from the Massachusetts Institute of Technology in 2005, under the mentorship of David Bartel.[3] He later received his post-doctoral training in David R. Liu's laboratory at the Harvard University from 2005 to 2008.[4] After completion of his post-doctoral training, Lawrence was affiliated with the Cancer Program of the Broad Institute, where he and his colleagues developed the MutSig algorithm,[1][2] which assesses the mutational significance by correcting for sources of mutational heterogeneity across cancer, including cancer type, mutational spectrum, gene expression, and replication timing.[5][6] The development of the MutSig algorithm led to the reanalysis of major cancer genome sequencing projects, including The Cancer Genome Atlas, to remove false positives that were present in previous studies.[7][8][9][10] In 2016, Lawrence was appointed as the assistant professor of pathology at the Harvard Medical School and the Assistant Geneticist at the Center for Cancer Research, Massachusetts General Hospital. Since 2017, Lawrence has been named Highly Cited Researcher in the field of Molecular Biology and Genetics by Clarivate.[11]

References

  1. ^ a b Lawrence, Michael S.; Stojanov, Petar; Polak, Paz; Kryukov, Gregory V.; Cibulskis, Kristian; Sivachenko, Andrey (June 16, 2013). "Mutational heterogeneity in cancer and the search for new cancer-associated genes". Nature. 499: 214–218. doi:10.1038/nature12213. PMC 3919509.
  2. ^ a b Lawrence, Michael S.; Stojanov, Petar; Mermel, Craig H.; Robinson, James T.; Garraway, Levi A.; Golub, Todd R. (January 5, 2014). "Discovery and saturation analysis of cancer genes across 21 tumour types". Nature. 505: 495–501. doi:10.1038/nature12912. PMC 4048962.
  3. ^ Lawrence, Michael S. (May 27, 2005). RNA polymerase ribozymes (PDF) (Thesis).
  4. ^ Lawrence, Michael S.; Phillips, Kevin J.; Liu, David R. (August 1, 2007). "Supercharging Proteins Can Impart Unusual Resilience". Journal of the American Chemical Society. 129 (33): 10110–10112. doi:10.1021/ja071641y. PMC 2820565.
  5. ^ Watson, Ian R.; Takahashi, Koichi; Futreal, P. Andrew; Chin, Lynda (September 11, 2013). "Emerging patterns of somatic mutations in cancer". Nature Reviews Genetics. 14: 703–718. doi:10.1038/nrg3539. PMC 4014352.
  6. ^ "MutSig on Biowulf". National Institutes of Health.
  7. ^ Ledford, Heidi (June 17, 2013). "Lists of cancer mutations awash with false positives". Nature. doi:10.1038/nature.2013.13206.
  8. ^ The Cancer Genome Atlas Research Network (September 26, 2013). "The Cancer Genome Atlas Pan-Cancer analysis project". Nature Genetics. 45: 1113–1120. doi:10.1038/ng.2764. PMC 3919969.
  9. ^ Dan Cossins. "Identifying Spurious Cancer Mutations". The Scientist.
  10. ^ John Timmer. "Cancer gene sequencing effort struggles through waves of false IDs". Ars Technica.
  11. ^ "Web of Science ResearcherID: AAC-8202-2020". Web of Science.