Accession Number:

AD1028419

Title:

Inferring Microbial Fitness Landscapes

Descriptive Note:

Technical Report,01 Oct 2012,30 Sep 2015

Corporate Author:

University of Pennsylvania Philadelphia United States

Personal Author(s):

Report Date:

2016-02-25

Pagination or Media Count:

16.0

Abstract:

Microbes and viruses evolve. Their evolution is often more rapid and of greater practical importance than our own evolution. How can we understand, or even predict, the evolutionary trajectory of microbes as they adapt For example, what determines how quickly, and by what specific mutations, avian influenza viruses will adapt to novel human hosts or how readily infectious bacteria will escape antibiotics or the human immune system In this research program we seek to combine mathematical models and statistical techniques to tackle this problem head-on to infer from data the determinants of microbial evolution with sufficient resolution that we can quantify their evolutionary trajectories, and sometimes even predict the details of their evolution.

Subject Categories:

  • Microbiology

Distribution Statement:

APPROVED FOR PUBLIC RELEASE