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Hannah Carter

Hannah Carter

Appointment

  • CIFAR Azrieli Global Scholar 2017
  • Genetic Networks

Institution

  • University of California San Diego
Department of Medicine, Division of Medical Genetics

Country

  • United States

Education

PhD (Biomedical Engineering), Johns Hopkins University
MEng (Electrical and Computer Engineering), University of Louisville
BS (Electrical and Computer Engineering), University of Louisville

About

Hannah Carter uses computation to study the role of genetic variation in cancer, for applications in precision medicine.

Her research is divided between efforts to understand how inherited variation shapes individual cancer risk, and how tumour-associated DNA mutations impact intracellular biological processes and cellular behaviours. Carter has demonstrated that acquired mutations in tumour genomes frequently affect specific protein-protein interactions. She has also uncovered new ways in which the inherited genome influences the probability that a particular cancer gene will acquire a mutation during tumour development. One of Carter’s current projects uses statistical modelling to investigate the extent to which the inherited immune system contributes to differences in cancer predisposition and outcome. A second project uses graphical modelling techniques to study the combined consequences of cancer mutations.

Awards

Johns Hopkins University Alumni Outstanding Recent Graduate Award, 2015
NIH Director’s Early Independence Award, 2013
Siebel Scholar, 2012
NDSEG Research Fellowship, 2008
Samuel T. Fife Outstanding Graduate Award, 2005

Relevant Publications

Marty, R. et al. "MHC-I genotype restricts the oncogenic mutational landscape." Cell 171, no. 6 (November 2017): 1272–1283.
Carter, H. et al. "Interaction Landscape of Inherited Polymorphisms with Somatic Events in Cancer." Cancer Discov. 7, no. 4 (April 2017): 410–23.
Engin, B., J. Kreisberg, and H. Carter. "Structure-based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces." PLoS One 4, no. 11 (April 2016): e0152929.
Engin, B., M. Hofree, and H. Carter. "Identifying Mutation-Specific Cancer Pathways Using a Structurally Resolved Protein Interaction Network." Pac Symp Biocomput. 20 (2015): 84–95.
Carter, H. et al. "Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations." Cancer Res 69, no. 6660 (August 2009).

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