The Sartor lab develops bioinformatics methods and tools for the analysis of high-throughput genome-wide regulatory and epigenomics data, and focuses on understanding the biological/clinical significance of results. The biological focus is cancer, specifically head and neck squamous cell carcinomas with a focus on human papillomavirus (HPV)-related cancers.

Our overall aim is to help all people lead a balanced, happy, safe, healthy, and meaningful life. This includes our current and previous lab members, all students in our graduate program, collaborators and colleagues, our families and friends, people who are very different from ourselves, and society overall. 

Our research aims to help cancer patients and to provide tools that can be used to advance the prevention and treatment of many diseases. Our main source of motivation to perform high quality, rigorous research stems from contributing to a better society. Because of this, we value cooperation within and between labs more than competition. 

We make a strong effort to understand those who are different from ourselves, and strive to provide a safe welcoming environment for all.

We adopt the Michigan Medicine Core Values of: 

1. Caring - Treat everyone with dignity, kindness and respect, promoting the well-being of self and others. 

2. Integrity - Adhere to the highest ethical standards, practicing truth and transparency in my words and actions. 

3. Teamwork - Work together with a shared purpose where each voice is encouraged, respected and valued. 

4. Innovation - Promote a culture of creativity that inspires new ideas and ways of thinking and behaving.

• Ph.D., Biostatistics, University of Cincinnati, 2007

• M.S., Biomathematics, North Carolina State University, 2000

• B.S., Mathematics, minors in Biology and Computer science, Xavier University, 1998

• BIOINF-500: Skills to Succeed in the Bioinformatics Graduate Program

• BIOSTAT-646 / BIOINF545: High Throughput Molecular Genomic and Epigenomic Data Analysis (2011-2019)

• BIOINF-527: Introduction to Bioinformatics - Lectures on statistics, gene expression and ChIP-seq data

• BIOINF-575: Programming in Bioinformatics - Section on programming in R (2011-2017)

• Girls Who Code: Faculty Advisor (starting 2017)

• Online Python and R courses: https://www.datacamp.com