Ph.D., University of Washington, Physics, 1986.
M.S., University of Washington, Physics, 1983.
Diplom in Physik (equiv. MS), University of Tuebingen, 1982.
My lab focuses primarily on the development of biomathematical descriptions of carcinogenesis, the identification and characterization of relevant spatio-temporal scales, and their impact on cancer incidence. From these descriptions we derive methods for the quantitative analysis of both experimental and epidemiological data, including data on precursor lesions from screening studies. The ultimate goal is to being able to model/optimize the benefits of cancer screening, prevention, and intervention - based on a biological description of the natural history of cancer.
Highlights of recent activities: investigation of mathematical and statistical properties of the Multistage Clonal Expansion (MSCE) carcinogenesis model, derivation of hazard functions (used to estimate the age-specific cancer incidence/mortality), development of fast algorithms for the computation of hazard and survival functions for constant and piecewise constant parameters, exploration of parameter identifiability, stable reparameterizations. We are also working on model extensions that capture more biological detail of neoplastic progression, including the spatial organization of normal and neoplastic tissues.
Highlights of past activities: radiation-induced carcinogenesis, multistage carcinogenesis as a framework to model the benefits of screening, interventions and cancer prevention strategies, multiscale modeling of neoplastic progression in colon and in Barrett's esophagus, stochastic modeling of DNA methylation and its somatic inheritance. These activities include the development of new computational approaches, high-performance (parallel) computing, hierarchical Bayesian models, and Markov Chain Monte Carlo (MCMC) techniques.
Much of the computer code we develop is in High Performance Fortran (HPF), which allows for parallelization of code on multiprocessor systems. We have set up two Beowulf clusters (the first at FHCRC!) running under Linux with dynamic load balancing using MOSIX. This configuration has been essential for the analysis of very large data sets.
I have extensive experience in scientific and statistical computing. My preferred programming environment for prototyping code and for statistical problems is R (a clone of S). I am author of the Bhat package, a set of tools written in F90 and R for the exploration of general likelihood functions (found at http://cran.r-project.org ).
Computational and Theoretical Biology. Development of a Center for Experimental and Mathematical Oncology (CEMO) jointly with Kristin Swanson (UW Pathology and Applied Mathematics).
Further topics of interest are:
Epigenetics and DNA Methylation. See our publication in JTB on the "Dynamics, Stability and Inheritance of somatic DNA Methylation Imprints."
Phylogenetics. In collaboration with Dr. Li Hsu (FHCRC), I have developed R-based software to explore SNP/LOH data and to construct maximum weight spanning trees based on Desper's algorithm. We are currently working on stochastic extensions of this approach.
Our mathematical models of carcinogenesis are useful tools for biologically informed cancer risk prediction and quantitative risk assessment of environmental carcinogens.
Reading, Writing, Speaking
English: Fluent, Fluent, Fluent
German: Fluent, Fluent, Fluent
French: Functional, Basic, Basic
2006-2013, Associate Member, Fred Hutchinson Cancer Research Center, Public Health Sciences Division
2002-2006, Assistant Member, Fred Hutchinson Cancer Research Center, Public Health Sciences Division
1993-2002, Senior Staff Scientist, Fred Hutchinson Cancer Research Center, Public Health Sciences Division
1988-1993, Staff Scientist, Fred Hutchinson Cancer Research Center, Public Health Sciences Division
1986-1988, Postdoctoral Fellow, Niels Bohr Institut, Copenhagen
Time-series analyses of air pollution and mortality in the United States: a subsampling approach.. Environmental health perspectives. 121(1):73-8.. 2013.
Impact of Tumor Progression on Cancer Incidence Curves.. Cancer research.. 2012.
Number and size distribution of colorectal adenomas under the multistage clonal expansion model of cancer.. PLoS computational biology. 7(10):e1002213.. 2011.
Biomarker-based early cancer detection: is it achievable? Science translational medicine. 3(109):109fs9.. 2011.
Multiscale estimation of cell kinetics.. Computational and mathematical methods in medicine. 11(3):239-54.. 2010.
Preneoplastic lesion growth driven by the death of adjacent normal stem cells.. Proceedings of the National Academy of Sciences of the United States of America. 105(39):15034-9.. 2008.
Age-specific incidence of cancer: Phases, transitions, and biological implications.. Proceedings of the National Academy of Sciences of the United States of America. 105(42):16284-9.. 2008.
Evaluation of screening strategies for pre-malignant lesions using a biomathematical approach.. Mathematical biosciences. 213(1):56-70.. 2008.
Does folic acid supplementation prevent or promote colorectal cancer? Results from model-based predictions. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 17(6):1360-7.. 2008.
Age effects and temporal trends in adenocarcinoma of the esophagus and gastric cardia (United States).. Cancer causes & control : CCC. 17(7):971-81.. 2006.