H Robert Frost, PhD
Assistant Professor of Biomedical Data Science
Assistant Professor of Molecular and Systems Biology
Associate Director of Quantitative Biomedical Sciences Graduate Program
Biomedical Data Science
Molecular and Systems Biology
Dartmouth College, Ph.D., 2014
Stanford University, MS, 1995
Stanford University, BS, 1993
Molecular and Cellular Biology Graduate Programs
Norris Cotton Cancer Center
Quantitative Biomedical Sciences
Hanover NH 03755
Office: Rubin 704
My research focuses on the development of bioinformatics and biostatistics methods for analyzing high-dimensional genomic data. Areas of statistical interest include dimensionality reduction (e.g., PCA), hypothesis aggregation (e.g., gene set testing), and penalized estimation (e.g., LASSO penalized regression). Areas of biological interest include cell signaling, tissue-specific gene activity, tumor immunology, and cancer prognosis prediction.
NIH grants R35GM146586 and R21CA253408
QBS 120: Foundations of Biostatistics I, Statistical Theory for the Quantitative Biomedical Sciences
Cell type-specific interaction analysis using doublets in scRNA-seq.
STREAK: A supervised cell surface receptor abundance estimation strategy for single cell RNA-sequencing data using feature selection and thresholded gene set scoring.
Characterizing control of memory CD8 T cell differentiation by BTB-ZF transcription factor Zbtb20.
SPECK: an unsupervised learning approach for cell surface receptor abundance estimation for single-cell RNA-sequencing data.
Reconstruction Set Test (RESET): a computationally efficient method for single sample gene set testing based on randomized reduced rank reconstruction error.
Tumor type and cell type-specific gene expression alterations in diverse pediatric central nervous system tumors identified using single nuclei RNA-seq.
Cell type-specific Interaction Analysis using Doublets in scRNA-seq (CIcADA).
Promiscuous evolution of Group A Streptococcal M and M-like proteins.
Intraoperative plasma proteomic changes in cardiac surgery: In search of biomarkers of post-operative delirium.
CAMML with the Integration of Marker Proteins (ChIMP).