My research spans epidemiology, biostatistics, bioinformatics, and computational biology, so can offer a variety of research opportunities for students and interns with an interest in data analysis or scientific software development, particularly using R and Bioconductor. This page provides project narratives my current grants; for more information see the NIH reporter.
EXPLOITING PUBLIC METAGENOMIC DATA TO UNCOVER CANCER-MICROBIOME RELATIONSHIPS
NIH Project #1U01CA230551 (role: PI). The human microbiome is implicated in the development and response to treatment of some cancers, including infectious agents estimated to be responsible for ~18% of the global cancer burden. This project improves the ability to identify new roles of the human microbiome in cancer by 1) enabling comprehensive comparisons of microbiome studies to previously published results and known microbial physiology, 2) developing higher- resolution approaches to identifying viruses and bacterial strains from metagenomic shotgun data, and 3) making all methods and resources easily usable by a broad research community. This project involves collaboration with other faculty at CUNY SPH, Harvard Medical School, Harvard School of Public Health, and the University of Trento (Italy).
CANCER GENOMICS: INTEGRATIVE AND SALABLE SOLUTIONS IN R/BIOCONDUCTOR
NIH Project #2U24CA180996 (role: co-PI). Researchers collect diverse types of complex genetic information about factors that contribute to cancer. This proposal provides software and data resources to help researchers manage and analyze this information using advanced computational and statistical approaches. This project involves collaboration with Roswell Park Comprehensive Cancer Center, Harvard Medical School, and the University of Padova (Italy).
IMPLEMENTING THE GENOMIC DATA SCIENCE ANALYSIS, VISUALIZATION, AND INFORMATICS LAB-SPACE (ANVIL)
NIH Project #5U24HG010263 (role: co-PI). The goal of this project is to create a cloud-based computational analysis and visualization workspace for genomic research. The research enabled by this workspace will accelerate our understanding of the genetic components of human health and disease and progress towards precision genomic medicine. This project brings my lab together with a consortium of genomics researchers from all over the country. More information.