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August 17-18, 2017 | Toronto, Canada
ANNUAL BIOTECHNOLOGY CONGRESS
Ann Biol Sci, 2017
ISSN: 2348-1927
E
xperimental evolution of RNA (or DNA) is a powerful
method to isolate sequences with useful function (e.g.,
catalytic RNA), discover fundamental features of the
sequence-activity relationship (i.e., the fitness landscape),
and map evolutionary pathways or functional optimization
strategies. However, the limitations of current sequencing
technology create a significant undersampling problem
which impedes our ability to measure the true distribution
of unique sequences. In addition, synthetic sequence
pools contain a non-random distribution of nucleotides.
We present and analyze simple models to approximate
the true sequence distribution. We also provide tools that
compensate for sequencing errors and other biases that
occur during sample processing.
Speaker Biography
Ramon Xulvi-Brunet has completed his PhD in Theoretical Physics from Humboldt
Universitaet zu Berlin, Post-doctoral Position in Applied Mathematics from University
of Sydney, Post-doctoral Position in Biostatistics from University of Pennsylvania and
Post-doctoral Position in Modelization of Biological Systems from Harvard University.
He is a Research Scientist at University of California Santa Barbara and also serves as
Physics Professor.
e:
ramon.xulvi@epn.edu.ecQuantitative characterization of RNA fitness landscapes
Ramon Xulvi-Brunet
National Polytechnic School, Ecuador
Ramon Xulvi-Brunet, Ann Biol Sci, 2017, 5:3
DOI: 10.21767/2348-1927-C1-002