Evolution, Antibiotics, and Algorithms
, Harvard Medical School
Date: Wednesday, April 01, 2015
Time: 11:30 AM to 1:00 PM Note: all times are in the Eastern Time Zone
Refreshments: 11:15 AM
Host: Bonnie Berger
Contact: Patrice Macaluso, 617-253-3037, firstname.lastname@example.org
Speaker URL: None
email@example.com, firstname.lastname@example.org, email@example.com
TALK: Evolution, Antibiotics, and Algorithms
Understanding the dynamics of microbial evolution has emerged as a central challenge in biology and biocomputation. Modeling and manipulating this process will be critical to our ability to effectively combat the rapid growth of antibiotic-resistant pathogens, as well as to our capacity to fully realize the technological potential of the microbial world.
Microbial evolution is as complex as the organisms it operates on, so both querying and manipulating it is greatly aided by algorithmically guided experimental approaches. Further, the large datasets generated by modern experiments themselves lead to new computational challenges.
In this talk, I will discuss three interwoven examples of how this combined experimental and computational approach can yield advances in basic science, bioengineering, and algorithms. In the first section of the talk, I will describe a new, inexpensive, and simple experimental apparatus to study bacterial evolution in spatially structured environments. Using it, we have been able to probe previously elusive aspects of the evolution of antibiotic resistance. Second, I will discuss how the statistics of mutations affect our ability to manage the evolution of antibiotic resistance. Finally I will introduce the framework of compressive genomics: using simple insights from evolution to compress the exponentially increasing amount of genomic data and compute natively on the compressed data, vastly improving the scaling of analyses of large genomic datasets.
Created by Patrice Macaluso at Wednesday, March 25, 2015 at 10:25 AM.