BIOGRAPHICAL SKETCH
Provide the following information for the Senior/key personnel and other significant contributors.
Follow this format for each person. DO NOT EXCEED FOUR PAGES.
NAME
POSITION TITLE
Johnson, W. Evan
Assistant Professor of Statistics
eRA COMMONS USER NAME (credential, e.g., agency login)
WEJOHNSON
EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and
residency training if applicable.)
DEGREE
INSTITUTION AND LOCATION
MM/YY
FIELD OF STUDY
(if applicable)
Southern Utah University, Cedar City, UT
Brigham Young University, Provo, UT
Harvard University, Cambridge, MA
Harvard University, Cambridge, MA
B.S.
M.S.
M.A.
Ph.D.
05/02
08/03
06/06
06/07
Mathematics
Statistics
Biostatistics
Biostatistics
A. Personal Statement
The development of personalized treatment regimes is an active area of current research in genomics. The
focus of our research is to investigate core biological components that contribute to disease prognosis and
development, and to develop latent variable models to accurately determine optimal therapeutic regimens for
individual patients. Because biological processes do not act in isolation but as parts of complex interactive
systems, we are computationally evaluating interactions between these systems at multiple levels. At the
sequence and cellular level, we have developed latent variable models for probabilistically determining gene
expression profiles that are linked to individual response to treatment. In addition, we are experimentally
perturbing subcomponents of larger biological systems or pathways and linking pathway activation status to
genetic disease risk and drug sensitivity. To accomplish this aim, we are developing adaptive Bayesian
regression, factor analysis, and structural equation models that integrate this in vitro experimental data into our
models while still allowing for the refinement and adaptation of pathway profiles within each dataset, efficiently
accounting for cell-type specific pathway differences or any “rewiring” do to cancer deregulation. Our ultimate
goal is to develop a comprehensive and integrated set of relevant, biologically interpretable computational tools
for genomic studies in personalized medicine. We are currently working on a variety of applications using data
from high-risk breast cancer cohorts, including the data from the Cancer Genome Atlas, ISPY2 trial, and other
tissue resources available at our collaborating institutions.
B. Positions and Honors
Positions and Employment
2002-2003
Teaching Assistant, Department of Statistics, Brigham Young University
2003-2007
Teaching Assistant, Department of Biostatistics, Harvard University
2004-2007
Research Assistant, Dept of Biostatistics and Comp. Biology, Dana Farber Cancer Institute
2007-Present
Assistant Professor, Department of Statistics, Brigham Young University
2008-Present
Adjunct Assistant Professor, Department of Oncological Sciences, University of Utah
Other Experience and Professional Memberships
2004-Present
American Statistical Association, Biometrics Section
2006-Present
International Biometrics Society, ENAR/WNAR
2006-Present
Institute of Mathematical Statistics
2009-Present
International Society for Computational Biology
Honors
2003-2007
2004-2006
2006
NIH Pre-doctoral Traineeship in Cancer Research
Certificate of Distinction in Teaching, Harvard Biostatistics Department
Prior Alumni Fellowship, Alpha Chi Honor Society
2006
Award for Achievement in Instructional Technology, Harvard University
C. Selected Peer-reviewed Publications
Most relevant to the current application
1. Johnson WE, Li W, Meyer CA, Gottardo R, Carroll JS, Brown M, Liu XS. Model-based analysis
of tiling-arrays for ChIP-chip. PNAS. 2006; 103 (33): 12457-12462
2. Song JS, Johnson WE, Zhu X, Zhang X, Jiang N, Liu XS. Model-based analysis of two-color tiling
arrays. Genome Biology 2007; 8: R178. (Joint first author)
Additional recent publications of importance to the field (in chronological order)
1. Johnson WE, Li W, Meyer CA, Gottardo R, Carroll JS, Brown M, Liu XS. Model-based analysis
of tiling-arrays for ChIP-chip. PNAS. 2006; 103 (33): 12457-12462
2. Song JS, Johnson WE, Zhu X, Zhang X, Jiang N, Liu XS. Model-based analysis of two-color tiling
arrays. Genome Biology 2007; 8: R178. (Joint first author)
3. Johnson WE, Rabinovic A, Li C. Adjusting batch effects in microarray expression data using
Empirical Bayes methods. Biostatistics. 2007; 8(1): 118-127.
4. Gottardo R, Li W, Johnson WE, Liu XS. A flexible and powerful Bayesian hierarchical model for
ChIP-chip experiments. Biometrics. 2008; 64: 468-478.
5. Johnson WE, Liu XS, Liu JS. Doubly-Stochastic Continuous-Time Hidden Markov Analysis of Genome
Tiling Arrays. Annals of Applied Statistics. 2009; 3: 1183-1203.
6. Hollenhorst PC, Chandler KJ, Poulsen RL, Johnson WE, Speck NA, Graves BJ. DNA specificity
determinants associate with distinct transcription factor functions. PLoS Genetics. 2009; 5(12): e1000778.
7. Clement NL, Snell Q, Clement MJ, Hollenhorst PC, Purwar J, Graves BJ, Cairns BR, Johnson WE. The
GNUMAP algorithm: unbiased probabilistic mapping of oligonucleotides from next-generation sequencing.
Bioinformatics. 2010; 26 (1): 38-45.
8. Thyagarajan B, Blaszczak AG, Chandler KJ, Watts JL, Johnson WE, Graves BJ. ETS-4 Is a
Transcriptional Regulator of Life Span in Caenorhabditis elegans. 2010; PLoS Genetics 6 (9): e1001125.
9. Rai K, Sarkar S, Broadbent T, Voas M, Grossman KF, Dehghanizadeh S, Hagos F, Li Y, Toth RK,
Chidester S, Bahr TM, Johnson WE, Sklow B, Burt R, Cairns BR, Jones DA. DNA Demethylase Activity
Maintains Zebrafish Intestinal Cells in a Progenitor-like State Following Loss of APC. 2010; Cell 142 (6):
930-942.
10. Leek JT, Scharpf R, Corrada-Bravo H, Simcha D, Langmead B, Johnson WE, Geman D, Baggerly K,
Irizarry RA (2010). Tackling the widespread and critical impact of batch effects in high-throughput data.
Nature Reviews Genetics 11, 733-739.
11. Johnson WE, Welker NC, Bass BL. Dynamic linear model for the identification of miRNAs in nextgeneration sequencing data. 2011; Biometrics, To appear.
12. Warf MB, Johnson WE, Bass BL. Improved annotation of C. elegans microRNAs by deep sequencing
reveals structures associated with processing by Drosha and Dicer. 2011; RNA. To appear.
D. Research Support
Ongoing Research Support
P01 CA073992-11
Randall Burt (PI)
12/01/09-11/30/14
Molecular and Clinical Approaches to Colon Cancer Precursors (PPG)
The overall objective of this Program Project Grant is to identify and test new ways to prevent, detect, and treat
colon cancer through an increased understanding of the genetics, cell biology and pathogenesis of this
malignancy and its precursor lesion, the adenomatous polyp.
Role: Consultant
R01 HG005692
W. Evan Johnson (PI)
Statistical tools and methods for next-generation sequencing in epigenomics
06/01/10-05/31/15
The goal of this study is to develop of statistical and computational tools for the analysis of second generation
sequencing technologies with applications in epigenomics.
Role: Principle Investigator