**Abstract:**

An accelerated pace of discovery in biological sciences is
made possible by a new generation of computational biology and bioinformatics
tools. Computational biology and
bioinformatics are emerging fields that use and develop computer science
knowledge in order to provide solutions to important biological problems.
Recently emerged next generation sequencing is the revolutionary
high-throughput sequencing technology requiring critical need for efficient
software to analyze massively large sequencing data. Important challenges in
computational biology and bioinformatics arise from the large amounts of data,
the difficulty to construct accurate mathematical models, and the computational
complexity of the corresponding simulations. In this talk, I will describe these
challenges in general and explore new computational, analytical, and high
performance techniques for analyzing large-scale datasets generated from mixed
microbial communities. Specifically, I will present the Sigma algorithm
(Strain-level Inference of Genomes from Metagenomic Analysis,
http://sigma.omicsbio.org) for metagenomic biosurveillance and taxonomic
profiling. A novel Sigma probabilistic model was developed to identify and
quantify genomes using the read mapping approach. The computation of Sigma can
be scaled from desktops to supercomputers to achieve a short turnaround time
for very large metagenomic datasets. This allows a prompt response of a
metagenomic biosurveillance network to disease outbreaks using supercomputers. I will
conclude the talk by outlining my future research agenda for the next couple of
years.

Reception to precede at 3:30 p.m.