William Evan Johnson, PhD
Associate Professor
Boston University School of Medicine
Dept of Medicine
Computational Biomedicine

PhD, Harvard University
MA, Harvard University
MS, Brigham Young University



William Johnson specializes in computational biology and biostatistics, developing new tools to investigate disease prognoses and causes and to help determine effective regimens based on individual patients’ risk factors. He has published in the journals Cell, Proceedings of the National Academy of Sciences, Biometrics, Nature Reviews Genetics, Annals of Applied Statistics, and Biostatistics. His work has been funded by the NIH.

The focus of his group's research is to develop computational and statistical tools to investigate core components that contribute to disease prognosis and etiology, and for the accurate determination of optimal diagnostic, prognostic, and therapeutic regimens for individual patients. They are actively developing methods and software tools for data preprocessing, integration, and downstream analysis, and applying these tools in a variety of clinical and biomedical applications. Their work includes a balance between statistical methods development, algorithm optimization, and clinical application. Statistical innovation focuses on the development of clinically motivated tools that integrate linear modeling, Bayesian methods, factor analysis and structural equations models, Hidden Markov models, mixture models, dynamic programming, and high-performance parallel computing. This work has resulted in widely used tools and algorithms for profiling transcription factors (MAT, MA2C), preprocessing and integrating of genomic data (ComBat, BatchQC, SCAN-UPC), aligning sequencing reads (GNUMAP), developing multi-gene biomarker signatures (ASSIGN), and metagenomic profiling (PathoScope). They have successfully applied their tools in several biomedical and clinical scenarios, ranging from mechanistic studies and to precision genomics.

Associate Professor
Boston University School of Public Health
Biostatistics


Member
Boston University
Bioinformatics Graduate Program




REMOVING BATCH EFFECTS IN GENOMIC AND EPIGENOMIC STUDIES
05/01/2018 - 04/30/2022 (PI)
NIH/National Institute of General Medical Sciences
1R01GM127430-01

AN INTERACTIVE ANALYSIS TOOLKIT FOR SINGLE CELL RNA-SEQ IN CANCER RESEARCH
08/01/2017 - 07/31/2020 (PI)
NIH/National Cancer Institute
5U01CA220413-02

PREPROCESSING AND ANALYSIS TOOLS FOR HIGH-THROUGHPUT TECHNOLOGIES
09/01/2016 - 06/30/2019 (PI)
Dana-Farber Cancer Institute NIH NIGMS
5R01GM083084-12

DFCI BILLING AGREEMENT FOR YUQING ZHANG
09/01/2016 - 02/28/2018 (PI)
Dana-Farber Cancer Institute

INTEGRATIVE ANALYSES OF REFERENCE EPIGENOMIC MAPS AND APPLICATIONS
09/18/2014 - 08/31/2017 (PI)
NIH/National Institute of Environmental Health Sciences
5R01ES025002-02

INTEGRATIVE SIGNALING MODELS TO DECIPHER COMPLEX CANCER PHENOTYPES
08/08/2012 - 07/31/2017 (PI)
University of Utah NIH NCI
U01CA164720

BILLING AGREEMENT FOR HEATHER SELBY
07/01/2014 - 06/30/2017 (PI)
Dana-Farber Cancer Institute

STATISTICAL TOOLS AND METHODS FOR NEXT-GENERATION SEQUENCING IN EPIGENETICS
03/01/2012 - 02/29/2016 (PI)
NIH/National Human Genome Research Institute
5R01HG005692-05




Yr Title Project-Sub Proj Pubs
2018 Removing batch effects in genomic and epigenomic studies 1R01GM127430-01
2017 An interactive analysis toolkit for single cell RNA-seq in cancer research 1U01CA220413-01
2016 Integrative signaling models to decipher complex cancer phenotypes 4U01CA164720-05 4
2015 Integrative analyses of reference epigenomic maps and applications 5R01ES025002-02
2015 Integrative signaling models to decipher complex cancer phenotypes 5U01CA164720-04 4
2014 Integrative analyses of reference epigenomic maps and applications 1R01ES025002-01
2014 Integrative signaling models to decipher complex cancer phenotypes 5U01CA164720-03 4
2014 Statistical Tools and Methods for Next-Generation Sequencing in Epigenetics 5R01HG005692-05 18
2013 Integrative signaling models to decipher complex cancer phenotypes 5U01CA164720-02 4
2013 Statistical Tools and Methods for Next-Generation Sequencing in Epigenetics 5R01HG005692-04 18
Showing 10 of 14 results. Show All Results
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

  1. Zhao Y, Johnson WE. Exploring Host-Microbe Interactions in Lung Cancer. Am J Respir Crit Care Med. 2018 Jul 31. PMID: 30063838.
     
  2. Zhang Y, Jenkins DF, Manimaran S, Johnson WE. Alternative empirical Bayes models for adjusting for batch effects in genomic studies. BMC Bioinformatics. 2018 Jul 13; 19(1):262. PMID: 30001694.
     
  3. Griffin PJ, Zhang Y, Johnson WE, Kolaczyk ED. Detection of multiple perturbations in multi-omics biological networks. Biometrics. 2018 May 17. PMID: 29772079.
     
  4. Brady SW, McQuerry JA, Qiao Y, Piccolo SR, Shrestha G, Jenkins DF, Layer RM, Pedersen BS, Miller RH, Esch A, Selitsky SR, Parker JS, Anderson LA, Dalley BK, Factor RE, Reddy CB, Boltax JP, Li DY, Moos PJ, Gray JW, Heiser LM, Buys SS, Cohen AL, Johnson WE, Quinlan AR, Marth G, Werner TL, Bild AH. Publisher Correction: Combating subclonal evolution of resistant cancer phenotypes. Nat Commun. 2018 Feb 05; 9(1):572.View Related Profiles. PMID: 29402882.
     
  5. Goldberg LR, Kirkpatrick SL, Yazdani N, Luttik KP, Lacki OA, Keith Babbs R, Jenkins DF, Evan Johnson W, Bryant CD. Casein kinase 1-epsilon deletion increases mu opioid receptor-dependent behaviors and binge eating1. Genes Brain Behav. 2017 Sep; 16(7):725-738.View Related Profiles. PMID: 28594147.
     
  6. Rahman M, Macneil S, Jenkins DF, Johnson WE. Activity of distinct growth factor receptor network components in breast tumors uncovers two biologically relevant subtypes. Genome Medicine. 2017; 9(1). View Publication
  7. Kirkpatrick SL, Goldberg LR, Yazdani N, Babbs RK, Wu J, Reed ER, Jenkins DF, Bolgioni AF, Landaverde KI, Luttik KP, Mitchell KS, Kumar V, Johnson WE, Mulligan MK, Cottone P, Bryant CD. Cytoplasmic FMR1-Interacting Protein 2 Is a Major Genetic Factor Underlying Binge Eating. Biol Psychiatry. 2017 May 01; 81(9):757-769.View Related Profiles. PMID: 27914629; DOI: 10.1016/j.biopsych.2016.10.021;.
     
  8. Manimaran S, Selby HM, Okrah K, Ruberman C, Leek JT, Quackenbush J, Haibe-Kains B, Bravo HC, Johnson WE. BatchQC: interactive software for evaluating sample and batch effects in genomic data. Bioinformatics. 2016 Dec 15; 32(24):3836-3838. PMID: 27540268.
     
  9. Yazdani N, Shen Y, Johnson WE, Bryant CD. Striatal transcriptome analysis of a congenic mouse line (chromosome 11: 50-60Mb) exhibiting reduced methamphetamine sensitivity. Genom Data. 2016 Jun; 8:77-80.View Related Profiles. PMID: 27222804; DOI: 10.1016/j.gdata.2016.03.009;.
     
  10. Hilton SK, Castro-Nallar E, Pérez-Losada M, Toma I, McCaffrey TA, Hoffman EP, Siegel MO, Simon GL, Johnson WE, Crandall KA. Metataxonomic and Metagenomic Approaches vs. Culture-Based Techniques for Clinical Pathology. Front Microbiol. 2016; 7:484. PMID: 27092134; PMCID: PMC4823605; DOI: 10.3389/fmicb.2016.00484;.
     
Showing 10 of 58 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 58 publications over 13 distinct years, with a maximum of 13 publications in 2015

YearPublications
19871
20062
20072
20094
20103
20117
20124
20136
20145
201513
20165
20172
20184
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72 E. Concord St Evans Building
Boston MA 02118
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