COLLOQUIUM
Department of Computer Science and Engineering
University of South Carolina
 
Algorithmic Techniques Employed in the Detection and Characterization
of Global Evolutionary Forces

Douglas Raiford

Department of Computer Science and Engineering
Wright State University

Date: April 24, 2008
Time: 1530-1700 (3:30pm-5pm)
Place: Swearingen 3C02 (Chemical Engineering Conference Room)

Abstract

Functional selection is typically considered to be the dominant force
shaping proteome evolution. Mutations that give rise to changes in
protein structure can lead to alterations of function that affect
fitness. An evolutionary force that is less gene-centric and more
global in nature, metabolic efficiency, recently has been shown to
influence proteome evolution. Metabolic efficiency is the selective
advantage experienced by an organism when there is a tendency for its
proteins to utilize less biosynthetically expensive amino
acids. Similarly, it has long been recognized that there are global
evolutionary forces at work in genomic evolution. One such selective
force is translational efficiency.  When the mRNA is translated into
its resultant polypeptide chain the translational machinery must wait
at a given codon for the appropriate tRNA to arrive. When the codon
associated with the most abundant tRNA pool is utilized the
waiting-time is shorter and a faster translation rate is
achieved. This seminar will cover algorithmic and statistical methods
that can be used to detect and characterize these two global
evolutionary forces. These forces tend to be weak and easily obscured
by other trends and biases present in the data.  A major topic of
discussion in this presentation is the resilience of the described
approaches and how they go about disambiguating the global
evolutionary forces, even in the presence of competing factors

Douglas W. Raiford is a Ph.D candidate in Computer Science and
Engineering at Wright State University, Dayton, OH, and received his
B.S. and M.S. degrees in computer science from Wright State University
in 2002 and 2005, respectively. His research interests include
bioinformatics, investigating global forces involved in genomic and
protein evolution, codon usage bias, evolutionary computation, and
pattern recognition.