Fall Colloquium Series presents Professor Mihai Pop.
During the past few years we have witnessed dramatic advances in DNA sequencing and mapping technologies. These technologies generate data orders of magnitude faster, and at just a fraction of the costs previously possible. As a result, DNA sequencing is rapidly becoming a critical tool in many areas of biology research. At the same time, the wealth of data being generated is rapidly challenging the capacity of the computational infrastructure available to researchers. Also, as sequencing is being applied in new contexts, the resulting data cannot be effectively analyzed by existing computational tools.
In my talk I will describe recent research from my lab that addresses emerging computational challenges in the analysis of genomic data.
During the first half of the talk I will discuss several results we obtained in the broad area of string algorithms. These results include theoretical analyses of the computational complexity of genome assembly, the development of algorithms for inexact matching capable of rapidly processing large numbers of short DNA sequences, and the use of cloud computing infrastructure to "commodify" the computational analysis of large genomic data-sets.
In the second part of my talk I will focus on problems arising from metagenomics research - the genomic analysis of communities of microbes. I will present new algorithms we developed for metagenomic assembly, as well as initial results on using time-series data to infer and model the dynamic interactions between microbes inhabiting an environment.
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