Maureen A Sartor, MS, PhD
- Professor, Computational Medicine and Bioinformatics
- Professor, Biostatistics
- Co-Director, Bioinformatics Graduate Program
Maureen A. Sartor is a Professor in the Department of Computational Medicine and Bioinformatics, with a joint appointment in Biostatistics. She received her PhD in Biostatistics in 2007 from the University of Cincinnati. Her research interests are in developing bioinformatics methods, mainly for analysis and interpretation of high throughput regulatory and epigenomics data. Her research focuses on cancer epigenomics and biomarker discovery, particularly oral squamous cell carcinomas. She also has projects studying ALS and methods to predict chemical exposure-gene target interactions and prioritize disease-specific variant-gene target pairs.
- PhD, 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
Epigenomics, cancer, human papillomavirus (HPV), ALS
Her research interests are in developing bioinformatics methods, mainly for analysis and interpretation of high throughput regulatory and epigenomics data, and multi-omics analyses. Her research focuses on cancer epigenomics and biomarker discovery, particularly oral squamous cell carcinomas. She also has projects studying ALS and methods to predict chemical exposure-gene target interactions and prioritize disease-specific variant-gene target pairs.
Qin T, Lee C, Cavalcante RC, Orchard P, Yao H, Zhang H, Wang S, Patil S, Boyle AP, Sartor MA. Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data. Genome Biology. 2022. 23(1):105.
Qin T, Li S, Henry LE, Liu S, Sartor MA. Molecular tumor subtypes of HPV-positive head and neck cancers: biological characteristics and implications for clinical outcomes. Cancers. 2021; 13(11):2721.
Lee CT, Cavalcante RG, Lee C, Qin T, Patil S, Wang S, Tsai ZTY, Boyle AP, Sartor MA. Poly-Enrich: count-based methods for gene set enrichment testing with genomic regions. NAR Genom Bioinform. 2020; 2(1):lqaa006.
Liu S, de Medeiros MC, Fernandez EM, Zarins KR, Cavalcante RG, Qin T, Wolf GT, Figueroa ME, D'Silva NJ, Rozek LS, Sartor MA. 5-Hydroxymethylation highlights the heterogeneity in keratinization and cell junctions in head and neck cancers. Clin Epigenetics. 2020 Nov 17;12(1):175.
Koneva LA, Zhang Y, Virani S, Hall PB, McHugh JB, Chepeha DB, Wolf GT, Carey TE, Rozek LS, Sartor MA. HPV integration in HNSCC correlates with survival outcomes, immune response signatures, and candidate drivers. Mol Cancer Res. 2018; 16(1):90-102.
Cavalcante RG, Patil S, Park Y, Rozek LS, Sartor MA. Integrating DNA methylation and hydroxymethylation data with the mint pipeline. Cancer Res. 2017; 77(21):e27-e30.
Cavalcante RG, Sartor MA. annotatr: genomic regions in context. Bioinformatics. 2017; 33(15):2381-2383.
Zhang Y, Koneva LA, Virani S, Arthur AE, Virani A, Hall PB, Warden CD, Carey TE, Chepeha DB, Prince M, McHugh JB, Wolf GT, Rozek LS, Sartor MA. Subtypes of HPV-positive head and neck cancers are associated with HPV characteristics, copy number alterations, PIK3CA mutation, and pathway signatures. Clinical Can Res. 2016; 22(18):4735-45
Cavalcante RG, Patil S, Weymouth TE, Bendiskas KG, Karnovsky A, Sartor MA. ConceptMetab: a tool for exploring relationships among biologically-related compound sets. Bioinformatics. 2016; 32(10):1536-43.
Areas of Expertise: Biostatistics