Bin Zhu, Ph.D.

Investigator

Biostatistics Branch

NCI/DCEG

9609 Medical Center Drive
Room SG/7E618
Rockville, MD 20850

240-276-7420

zhub@mail.nih.gov

Research Topics

Dr. Bin Zhu integrates statistics and genomics to understand the etiology of mutational signatures and reveal tumor heterogeneity. He develops statistical methods/tools and leads the scientific investigations to:

  • Extract mutational signatures and characterize their etiologies across different study designs and platforms, and
  • Uncover inter- and intra-tumor heterogeneity with translational and clinical implications.

Software

Biography

Dr. Zhu received a Ph.D. in biostatistics from the University of Michigan in 2010 and then spent two years as a postdoctoral associate at the Department of Statistical Science and the Center for Human Genetics at Duke University. He joined the Biostatistics Branch of DCEG in 2012 as a tenure-track investigator.

Selected Publications

  1. Zhu B, Xiao Y, Yeager M, Clifford G, Wentzensen N, Cullen M, Boland JF, Bass S, Steinberg MK, Raine-Bennett T, Lee D, Burk RD, Pinheiro M, Song L, Dean M, Nelson CW, Burdett L, Yu K, Roberson D, Lorey T, Franceschi S, Castle PE, Walker J, Zuna R, Schiffman M, Mirabello L. Mutations in the HPV16 genome induced by APOBEC3 are associated with viral clearance. Nat Commun. 2020;11(1):886.
  2. Zhu B, Poeta ML, Costantini M, Zhang T, Shi J, Sentinelli S, Zhao W, Pompeo V, Cardelli M, Alexandrov BS, Otlu B, Hua X, Jones K, Brodie S, Dabrowska ME, Toro JR, Yeager M, Wang M, Hicks B, Alexandrov LB, Brown KM, Wedge DC, Chanock S, Fazio VM, Gallucci M, Landi MT. The genomic and epigenomic evolutionary history of papillary renal cell carcinomas. Nat Commun. 2020;11(1):3096.
  3. Lee D, Zhu B. A semiparametric kernel independence test with application to mutational signatures. J Am Stat Assoc. 2021;116(536):1648-1661.
  4. Lee D, Wang D, Yang XR, Shi J, Landi MT, Zhu B. SUITOR: Selecting the number of mutational signatures through cross-validation. PLoS Comput Biol. 2022;18(4):e1009309.

Related Scientific Focus Areas

This page was last updated on Friday, May 6, 2022