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OMB No. 0925-0001/0002 (Rev. 08/12 Approved Through 8/31/2015)
BIOGRAPHICAL SKETCH
Provide the following information for the Senior/key personnel and other significant contributors.
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NAME: Berman, Benjamin P
eRA COMMONS USER NAME (agency login): BENBERMAN
POSITION TITLE: Associate Professor
EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing,
include postdoctoral training and residency training if applicable.)
INSTITUTION AND LOCATION
DEGREE Completion Date
(if applicable)
MM/YYYY
University of California, Berkeley, CA BA
University of California, Berkeley, CA PhD
06/1996
12/2006
FIELD OF STUDY
Computer Science
Molecular & Cell Biology (Bioinformatics track)
A. PERSONAL STATEMENT
Dr. Berman leads the Bioinformatics and Computational Biology Research Center at Cedars-Sinai, and
his expertise includes cancer epigenomics, non-coding regulatory sequence annotation, and next-generation
sequencing technologies. From 2008-2014, he was Director of Bioinformatics for the USC Epigenome Center
Illumina Sequencing Core, where his group developed software pipelines to analyze ~3,000 samples per year,
including whole-genome bisulfite-seq (WGBS), ChIP-seq, RNA-seq, and others. There, he sequenced the first
complete DNA methylation map of cancer using WGBS, and collaborated to generate and analyze sequence
data as part of the ENCODE (Farnham, PI), PsychENCODE (Farnham, PI), and TCGA Consortia (Laird, PI).
He is currently the epigenomics working group lead for the International Cancer Genome Consortium PanCancer Analysis of Whole-Genomes (ICGC-PCAWG) Consortium. In 2014, Dr. Berman moved to Cedars-Sinai
Medical Center in Los Angeles to establish a new Center to develop computational pipelines for patientfocused genomics research.
B. POSITIONS AND HONORS
Positions and Employment
1996 - 1997
Software Engineer, Apple Computer, Cupertino, CA
1998 - 2000
Bioinformatics Software Engineer, HHMI / UC Berkeley, Berkeley, CA
2000 - 2006
Graduate Research Assistant, HHMI / UC Berkeley, Berkeley, CA
2007 - 2008
Postdoctoral Fellow, USC Norris Comprehensive Cancer Center, Los Angeles, CA
2008 - 2014
Sr. Research Assoc. & Director of Next-gen sequencing informatics, USC Epigenome Center
2011 - 2014
Assistant Professor of Bioinformatics, Dept. of Preventive Medicine, USC, Los Angeles, CA
2014 - present Associate Professor, Cedars-Sinai Medical Center, Los Angeles, CA
Director, Bioinformatics and Computational Biology Research Center
Other Experience and Professional Memberships
1998 Member, International Society of Computational Biology
2009 Member, American Association for Cancer Research
2013 Faculty member, F1000
2014 Ad hoc study section member NIH (GCAT, ITCR), CPRIT (cancer biology)
Honors
2001
2007
2010
2013
2013
NIH T32 Genomics predoctoral trainee, UC Berkeley
NIH T32 Cancer epidemiology postdoctoral fellow, UCLA/USC
Forbeck Scholar Award, William Guy Forbeck Research Foundation
Junior Faculty Institutional Research Award, American Cancer Society
Research Career Development Award, Stop Cancer!
C. CONTRIBUTIONS TO SCIENCE
References were selected from a total of 42 peer reviewed papers. My name is in bold (Berman BP) when I
played a first author or corresponding author role (* asterisks denote equal contribution).
For a list of all publications, see: http://www.ncbi.nlm.nih.gov/pubmed?term=berman-bp&cmd=search
I. Sequence grammar of transcriptional enhancers: Early studies by others had shown that transcriptional
enhancers acted as key regulators of metazoan gene regulation, and that short transcription factor binding
sites (TFBSs) were central to their function. As a graduate student, I was the first to show that these
properties could be used to predict enhancers genome-wide, predictions that were validated in vivo in fruitfly
embryos [a]. I next showed that this approach could be improved by incorporating phylogenetic conservation
of TFBSs [b]. I have continued to apply these principles in subsequent work in human cancer. Specifically, I
identified genome-wide alterations in AP1 binding sites in colon cancer [c], and extended this approach as an
unbiased bioinformatic screen to identify TFBS and reconstruct altered transcription factor networks in
primary tumors [d].
a. Berman BP, Nibu Y, Pfeiffer BD, Tomancak P, Celniker SE, Levine M, Rubin GM, Eisen MB.
Exploiting transcription factor binding site clustering to identify cis-regulatory modules involved in
pattern formation in the Drosophila genome. Proc Natl Acad Sci U S A. 2002 Jan 22;99(2):757-62.
PubMed Central PMCID: PMC117378. (594 citations)
b. Berman BP*, Pfeiffer BD*, Laverty TR, Salzberg SL, Rubin GM, Eisen MB, Celniker SE.
Computational identification of developmental enhancers: conservation and function of transcription
factor binding-site clusters in Drosophila melanogaster and Drosophila pseudoobscura. Genome
Biol. 2004;5(9):R61. PubMed Central PMCID: PMC522868. (227 citations)
c. Berman BP, Weisenberger DJ, Aman JF, Hinoue T, Ramjan Z, Liu Y, Noushmehr H, Lange CP,
van Dijk CM, Tollenaar RA, Van Den Berg D, Laird PW. Regions of focal DNA hypermethylation
and long-range hypomethylation in colorectal cancer coincide with nuclear lamina-associated
domains. Nat Genet. 2011 Nov 27;44(1):40-6. PubMed Central PMCID: PMC4309644. (231
citations)
d. Yao L, Shen H, Laird PW, Farnham PJ*, Berman BP*. (2015) “Inferring Regulatory Element
Landscapes and Transcription Factor Networks from Cancer Methylomes”. Genome Biology. 2015
May 21; 16(1):105. PubMed Central PMCID: PMC4460959 (3 citations)
II. Integrative epigenomics of cancer: As a postdoctoral fellow, I used genomic technologies and
computational methods to understand epigenetic changes in cancer. My 2008 study identified androgenresponsive enhancers in prostate cancer cells, and was significant for its pioneering approach of combining
multiple independent ChIP-chip marks to define combinatorial epigenomic signatures [e]. From 2009-2014, I
was the bioinformatics lead for the TCGA epigenomic data production group. There, I was a co-author on my
USC team’s landmark paper describing the novel epigenetic subtype gCIMP and associated IDH1 mutation
in gliomas [f], along with five other TCGA Consortium papers in Nature, Nature Genetics, and Cell (not
listed here). My 2011 paper ([d], above) was the first complete DNA methylation map of any cancer, and was
significant for its discovery that widespread epigenetic changes in cancer correspond to the 3D
organizational structure of the cell nucleus. I recently led a project with Dr. Peter Jones to map the
epigenomes of cancer cells deficient for key DNA methyltransferases, suggesting a primary driving role for
DNA methylation in the development of cancer [g].
e. Jia L*, Berman BP*, Jariwala U, Yan X, Cogan JP, Walters A, Chen T, Buchanan G, Frenkel B,
Coetzee GA. Genomic androgen receptor-occupied regions with different functions, defined by
histone acetylation, coregulators and transcriptional capacity. PLoS One. 2008;3(11):e3645.
PubMed Central PMCID: PMC2577007. (120 citations)
f. Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, Pan F, Pelloski CE,
Sulman EP, Bhat KP, Verhaak RG, Hoadley KA, Hayes DN, Perou CM, Schmidt HK, Ding L, Wilson
RK, Van Den Berg D, Shen H, Bengtsson H, Neuvial P, Cope LM, Buckley J, Herman JG, Baylin
SB, Laird PW, Aldape K. Identification of a CpG island methylator phenotype that defines a distinct
subgroup of glioma. Cancer Cell. 2010 May 18;17(5):510-22. PubMed Central PMCID:
PMC2872684. (985 citations)
g. Lay FD, Liu Y, Kelly TK, Witt H, Farnham PJ, Jones PA*, Berman BP*. (2015) “The role of DNA
methylation in directing the functional organization of the cancer epigenome”. Genome Research,
2015 Apr; 25(4):467. PubMed Central PMCID: PMC4381519. (7 citations)
III. Freely available epigenome analysis software: One of the most important contributions I can make is to
create user-friendly and freely available software tools. During my PhD research (2001-2006), I developed a
widely used and open-source web-based tool for enhancer identification in Drosophila ([a-b], above) as well
as a global database of embryonic gene expression in Drosophila [h]. My group has worked to make our
computational pipelines more accessible by providing versions for publicly available cloud computing
platforms [i], and open-source packages that use standardized frameworks such as BioConductor [j] (and the
ELMER package for transcriptional network reconstruction [d], above) and GATK [k].
h. Tomancak P*, Berman BP*, Beaton A, Weiszmann R, Kwan E, Hartenstein V, Celniker SE, Rubin
GM. Global analysis of patterns of gene expression during Drosophila embryogenesis. Genome
Biol. 2007;8(7):R145. PubMed Central PMCID: PMC2323238. (257 citations)
i. Juve G, Deelman E, Vahi K, Mehta G, Berriman B, Berman BP, Maechling P: “Scientific workflow
applications on Amazon EC2”. IEEE Conference on E-Science. 2009 Dec. 9-11, pp. 59-66. arXiv
ID:1005.2718 DOI:10.1109/ESCIW.2009.5408002 (191 citations)
j. Coetzee SG, Rhie SK, Berman BP, Coetzee GA, Noushmehr H. FunciSNP: an R/bioconductor tool
integrating functional non-coding data sets with genetic association studies to identify candidate
regulatory SNPs. Nucleic Acids Res. 2012 Oct;40(18):e139. PubMed Central PMCID:
PMC3467035. (34 citations)
k. Liu Y, Siegmund KD, Laird PW, Berman BP. Bis-SNP: combined DNA methylation and SNP calling
for Bisulfite-seq data. Genome Biol. 2012 Jul 11;13(7):R61. PubMed Central PMCID:
PMC3491382. (50 citations)
IV. Genomic technology development: As an undergraduate-level researcher, I developed computational
pipelines used in the sequencing of the Drosophila melanogaster genome [l,m], and I have continued to
innovate in the area of genomic technology development. In 2008, I conceived of and initiated a project to
identify cancer risk enhancers by combining high-density genomic tiling arrays of the c-Myc region with ChIPchip [n]. In 2010, I led a project with Dr. Peter Jones to develop a next-generation sequencing approach
(NOMe-seq) to measure genome-wide DNA methylation and chromatin accessibility within the same DNA
molecule [o]. NOMe-seq was named one of the top 10 innovations of the year by The Scientist (Dec. 2013;
v.27,p.38394).
l.
Adams MD, [191 authors including Berman BP], Rubin GM, Venter JC. The genome sequence of
Drosophila melanogaster. Science. 2000 Mar 24;287(5461):2185-95. PubMed PMID: 10731132.
(5,533 citations)
m. Hoskins RA, Nelson CR, Berman BP, Laverty TR, George RA, Ciesiolka L, Naeemuddin M,
Arenson AD, Durbin J, David RG, Tabor PE, Bailey MR, DeShazo DR, Catanese J, Mammoser A,
Osoegawa K, de Jong PJ, Celniker SE, Gibbs RA, Rubin GM, Scherer SE. A BAC-based physical
map of the major autosomes of Drosophila melanogaster. Science. 2000 Mar 24;287(5461):22714. PubMed PMID: 10731150. (143 citations)
n. Jia L, Landan G, Pomerantz M, Jaschek R, Herman P, Reich D, Yan C, Khalid O, Kantoff P, Oh W,
Manak JR, Berman BP, Henderson BE, Frenkel B, Haiman CA, Freedman M, Tanay A, Coetzee
GA. Functional enhancers at the gene-poor 8q24 cancer-linked locus. PLoS Genet. 2009
Aug;5(8):e1000597. PubMed Central PMCID: PMC2717370. (168 citations)
o. Kelly TK, Liu Y, Lay FD, Liang G, Berman BP*, Jones PA*. Genome-wide mapping of nucleosome
positioning and DNA methylation within individual DNA molecules. Genome Res. 2012
Dec;22(12):2497-506. PubMed Central PMCID: PMC3514679. (77 citations)
D. RESEARCH SUPPORT
Ongoing Research Support
2014/05/13-2017/04/30
U01 CA184826-01, National Cancer Institute (NCI)
PI(s): Berman, Benjamin P
Berman Role: PI
Software Tools For Regulatory Analysis of Large Cancer Methylome Datasets
Major Goals: Development of a user-friendly software toolkit to analyze large number of patient cancer DNA
methylation profiles, using non-coding gene regulatory databases from ENCODE and other public sources.
Collaboration with GALAXY software group at Johns Hopkins University.
2015/09/01-2018/08/31
Samuel Oschin Comprehensive Cancer Center (Cedars-Sinai internal)
PI(s): Benjamin Berman and Barry Stripp
Berman Role: PI
Defining Genome-Wide Gene Regulatory Changes In Individual Cell Types of Non-Small Cell Lung
Carcinomas
Major Goals: Use transcriptomic and epigenomic sequencing to profile normal lungs from donors and tumors
from NSCLC patients, in order to describe epigenetic changes to both cancer cells and the tumor
microenvironment at the single-cell level.
2012/09/01-2016/03/01
R01 HG006705, National Human Genome Research Institute (NHGRI)
PI(s): Kim Siegmund
Berman Role: Co-investigator
Statistical Analysis Methods for Epigenomic Data
Development of statistical methods for the analysis of DNA methylation data generated using whole-genome
bisulfite sequencing and Infinium methylation mircroarray.
Completed Research Support
2014/04/01-2015/03/31
R01 MH103346, National Institute of Mental Health (NIMH)
PI(s): James Knowles & Peggy Farnham
Berman Role: Co-investigator
The USC and LIBD PsychENCODE Consortium
Generate and integrate multi-dimensional epigenomic data (ChIP-seq, NOMe-seq, RNA-seq) in neuronal cell
culture models derived from individuals with schizophrenia and healthy controls. The Berman component will
use NOMe-seq for bioinformatic decomposition of mixed cell types within cultures.
2009/09/01-2014/07/01
U24 CA143882 , National Cancer Institute (NCI)
PI(s): Peter Laird & Steve Baylin
Berman Role: Co-investigator
The USC-JHU Cancer Epigenome Characterization Center (TCGA)
Major Goals: Data production and analysis of DNA methylation data for The Cancer Genome Atlas (TCGA)
tumor samples. Berman subproject: Whole-Genome Bisulfite Sequencing (WGBS) pilot for dozens of TCGA
samples.
2012/09/01-2014/09/01
R01 CA170550, National Cancer Institute (NCI)
PI(s): Peter Jones
Berman Role: Co-investigator
Epigenetic Drivers of Cancer
The goal of this project is to develop model system and computational models to distinguish epigenetic
changes driving cancer progression (i.e. “drivers”) from passenger changes.
2011/10/01-2014/09/01
R01 HL114094, National Heart, Lung, and Blood Institute (NHLBI)
PI(s): Ite Laird-Offringa & Zea Borok
Berman Role: Co-investigator
Epigenomic Profiling of Human Lung Alveolar Epithelium in Health
Generate and integrate multi-dimensional epigenomic data (ChIP-seq, FAIRE-seq, Bisulfite-seq) in primary
human lung cells that are trans-differentiated in culture to model reprogramming that occurs in normal (and
pathological) lung physiology.