I am a mathematical biologist interested in developing mathematically sound approaches to the analysis of high-throughput DNA sequencing data. To do this, I utilize and develop techniques from the fields of probability, compressed sensing, and optimization. I am particularly interested in developing methods to analyze genomic and metagenomic data.
We introduce a framework to compare tools utilized to determine what microbes are present in a sample, and at what relative abundance. This will help computational biologists design better tools to analyze communities of microorganisms (which affect nearly everything in existence!).
We show that read mapping, along with a probabilistic assignment of multi-mapped reads, outperforms other computational approaches to identify the presence and relative amount of viral and fungal organisms in a metagenomic sample of microorganismal DNA.
A description of the NIH NCATS culture that emerged during the Translator project.
The vision and high-level overview of the NIH National Center for Advancing Translational Science (NCATS) project entitled "Translator" (through which we have been funded). The goal of the project is essentially to build a biomedical "Siri": an automated platform for answering biomedical research questions that leverages repositories of publicly available information.
The Oregonian (a Portland-based newspaper) has featured our work in analyzing the blood microbiome of patients with and without mental disorders.