I am an Assistant Professor in the Division of Bioinformatics and Computational Biology in the Department of Medical Informatics and Clinical Epidemiology at OHSU (BCB/DMICE) and a member of the OHSU Knight Cancer Institute. My research focus is on the Systems Biology of Complex Diseases. I use integrative modeling approaches across OMICs types to achieve this.
With over fourteen years of bioinformatics experience, I have developed methods for low-level preprocessing and high-level analysis of many OMICs types, including expression (especially alternative splicing), phosphoproteomics, proteomics, and genomics. My experience in functional genomics has led me to use models such as Graphical Models and Networks to integrate these many OMICs types into building a unified picture of integrated systems-level dysregulation in complex diseases such as alcoholism and cancer.
I am also actively involved in teaching and utilizing interactive visualization, especially in the analysis of high-dimensional mass cytometry data.
PhD in Biomedical Informatics, 2014
Oregon Health & Science University
MS in Biomedical Informatics, 2004
Oregon Health & Science University
BA in Chemistry, 1998
I teach in the summer hybrid BMI569/669 Data Analytics course at OHSU (Hybrid course co-taught with Kaiser Permanente Data & Information Management Enhancement (DIME) group).
I am also a co-instructor for BMI551/651 Bioinformatics and Computational Biology II: Statistical Methods, providing drop-in sessions for R programming and general tutoring.
We are teaching an introductory bootcamp in Python called NEU640 Python Bootcamp for Neuroscientists.. This is a week-long course meant to introduce neuroscience students to the basics of python with data types familiar to them, including imaging and electrophysiology data. Taught with Stephen David, Brad Buran, Daniela Sadieri, Lucille Moore, Charlie Heller, Zack Schwartz. Winter Quarter, 2018.
I am also course co-director for HSMP/PHE410 Introduction to Health Informatics. at Portland State University. Spring Quarter, 2018.
I have a free online introductory course at DataCamp called the RBootcamp. In this course, we cover the basics of visualization, data munging, and basic statistics using the tidyverse in R. It is freely available to everyone, but registration is required.
I am currently developing a course called Statistical Analysis of Networks in R for DataCamp. More info as it develops.
I have developed a number of self-directed training materials for learning R and specific packages that I’ve found useful. Most of these are available from my github page and may be used freely by students.
tidyversefor manipulating data in R. You will need to register on DataCamp. This interactive course was written with both Jessica Minnier and Chester Ismay.
Many of these tutorials have been given through the student club at OHSU that I mentor, called BioData Club. They are all freely available to be reused by other instructors.
As a developer and programmer of R, I enjoy teaching others about the basics of data wrangling and analysis. Here are a few of the tutorials I’ve put together.
tidyversein R. With Eric Leung.
ggplot2and the grammar of graphics.
ggvis, which adds extra interactivity to
shinyplots using the magic of vega.
dplyrfor interactive graphics.
As an instructor under OHSU’s Big Data To Knowledge (BD2K) Training Grant, I have also developed the following short workshops to encourage students to explore data and learn the basics of data-wrangling.
shinyfor exploratory data analysis and
caretfor machine learning. Part 1 and Part 2.
I have a parallel career as a composer and performing musician. I started taking cello lessons when I turned 30. I’m a lifelong learner and I love to play with and accompany other musicians. For more information, please see my artist webpage.