Profile
My research interests include modeling high-dimensional data “-omic” data. Specifically, I create integrated models of transcriptomic, lipomic and metabolomic profiles to predict dietary and health outcomes. The application of my research is for personalized and translational medicine. I am currently a bioinformatics PhD candidate at the University of Michigan and my advisor is Dr. Charles Burant, MD, PhD. Keywords: Biostatistics, Bioinformatics, Metabolomics, Personalized Medicine, High-throughput Data, High Dimensional Data, Integrative Physiology, Kinetic Systems Biology
Education
University of Michigan, Ann Arbor, MI 48109
Bioinformatics, PhD. 2008 - present.
Achieved Candidacy May 2009.
Advisor: Dr. Charles C. Burant, MD, PhD
Co-advisor: Dr. Santiago Schnell
University of Michigan, Ann Arbor, MI 48109
Biostatistics, MS. 2006 - 2008.
Advisors: Dr. Debashis Ghosh and Dr. Charles Burant
Case Western Reserve University, Cleveland, OH 44106
Economics, Evolutionary Biology, minor in Mathematics, BA. 2002 - 2006.
Advisors: Drs. Robert Slonim and Patricia Princehouse
Experience
Research Assistant, U of Mich. Dept of Internal Medicine
Genomic, metabolomic, transcriptomic and lipomic data analysis under the guidance of my advisor, Dr. Charles Burant. The focus is on the development and validation of systems biological models of metabolic function.
Research Assistant, U of Mich. Dept of Biostatistics
Genomic data analysis and bioinformatics under the guidance of Professor Debashis Ghosh. My projects included modeling changes in gene expression in Drosophila melanogaster using multiple genome-wide studies. I also did data analysis of microarray experiments using R and Bioconductor.
Intern, National Institutes of Health,
Center for Information Technology,
Division of Computational Bioscience, Bethesda, MD. Summer 2005.
Exploratory data analysis and modeling under the guidance of Drs. James Malley, Lawrence Brody and Tyra Wolfberg. I concentrated on several projects involving statistical genomics and feature discovery via machine learning. The data consisted of lists of exons from many species and related sequence information (percent identity, amino acid frequences, etc). We uncovered several novel results using methods of statistical learning machines, specifically Random Forests and closely related methods for rigorous classification error estimation and model validation.
Research Assistant, Case Western Reserve University Dept of Economics, Cleveland, OH. 2003 - 2006.
I worked with my advisor, Professor Robert Slonim, in conducting behavioral economics experiments on human subjects. Of particular interest were gender differences in risk aversion and attitudes about fairness.
Research Assistant, Case Western Reserve University Dept. of Sociology, Cleveland, OH. 2002 - 2006.
I worked closely with a group of healthcare sociologists on a longitudinal study of health outcomes in frail, elderly veterans. My responsibilities included data entry, general research organization and conducting telephone interviews with the veterans.
Fellowships and Awards
- Omicron Delta Epsilon, economics honors society. Inducted in 2005.
- NIH Training Grant in Cellular and Molecular Basis of Systems Biology. July 1, 2009 - 2010. The goal of this training grant is to provide graduate students with a broad training in the application of cellular and molecular technique to the study of problems in systems and integrative biology. The training grant is based in the department of Integrative Physiology, but includes faculty from other departments.
Service
- Mentor for young women in math through The Association for Women in Mathematics mentoring program. 2009 to Present.
- Tutor at 826Michigan, a non-profit organization dedicated to supporting students aged 6 to 18 with their creative and expository writing skills, and to helping teachers inspire their students to write. I tutored at West Middle School in Ypsilanti, MI. Spring 2009.
Presentations
“A Systems Biology Approach to Drug-target Discovery in Human Metabolic Diseases”
Candidacy Defense. Spring 2009.
“An Introduction to R”
Biostatistics brownbag seminar. Winter and Spring 2007, Winter 2008.
“Integration of Genomic Data in Drosophila melanogaster”
Michigan Student Symposium for Interdisciplinary Statistical Science, 2007.
“Gender Differences in Risk Aversion and Competitiveness”
Economics Honors Thesis, 2006.
Skills
I strongly believe that publicly funded science should be conducted with publicly available resources to promote code sharing and reproducibility. For that reason, all of my primary research is done using freely downloadable tools. I do all of my data analysis with R, a free, open-source statistical suite. I also use Python (more specifically, BioPython), which is free.
Programming Languages: R, Python, C, C++
Software: Ingenuity Pathway Analysis, FANMOD, Genomatix, R, Bioconductor, Ggobi, ggplot2, GIMP, Ubuntu Linux, Mac OS X, Windows
Relevant Coursework
From the University of Michigan:
Linear Models, Probability Theory, Survival Analysis, Generalized Linear Models, Statistical Inference, Categorical Data Analysis, Longitudinal Data Analysis, Statistical Genetics, Epidemiology, Human Genetics, Sequence Alignment/Analysis, SAS Programming, Bioinformatics, C++ Programming, Physiology, Design and Analysis of Clinical Trials, Algorithms in C++, Microarray Data Analysis
From Coursera:
In addition to the coursework required for the partial fulfillment of my master of science and doctoral degrees, I am actively participating in free online courses offered through Coursera. At present, I have taken a course in Probabilistic Graphical Models, and am enrolled for several more including a calculus refresher, network theory and sociology. Thus far, I have found Coursera to be an extremely satisfying way to learn new skills and methods in a non-traditional environment. I have also found it to be an amazing venue in which to learn material from fields outside of my own, which was unavailable to me in the conventional university setting.
