• publication
    Sunday, July 2, 2017

    A gene regulatory network is basically a representation of how genes interact with each other. In this work, we develop the only (to date) method to assess the accuracy of so called "motif discovery algorithms" that seek to find important sub-networks of a given gene regulatory network. We develop a provably correct mathematical approach (based on a variety of metrics that say how close two matrices are to each other) and use this to assess the performance of a variety of motif discovery algorithms.

  • Basic page

    I'm a mathematical biologist who is interested in developing mathematically sound approaches to the analysis of high-throughput DNA sequencing data.

  • Basic page

    The BioRxiv is an alternative to the arXiv aimed at more "computational biology" oriented scientists.

  • Basic page

    This image is formed by using the most frequent words used when considering all of my publications.

  • publication
    Tuesday, May 1, 2012

    This is my PhD thesis from Penn State (advised by Manfred Denker).

Improving Min Hash for Metagenomic Classification

A presentation about work with Hooman Zabeti that used probabilistic data analysis to analyze metagenomic communities.

MTH 321: Introductory applications of mathematical software

This is a course that I created back in 2014 (that continues to run, typically in the Fall and Spring) to introduce students to Mathematica, Matlab, and LaTeX. In the future, I will be incorporating modules on Python and/or Julia. This hands-on course has been attended by over 80 undergradutes, as well as a handfull of graduate students and faculty as well!

I wrote a (~200 page) textbook to accompany this course which can be found here.

MetaPalette Summary video

Very brief explanation of how MetaPalette works.