Consulting Projects - Spring 2004

The Standard Genetic Code Enhances Adaptive Evolution of Proteins

*March 11-21, 2004*

*Clients:* Wen Zhu and Dr. Stephen Freeland, Department of Biological Sciences, UMBC

*Consultant:* Dr. Matthias K. Gobbert, Mathematics

*Description:*
The standard genetic code, by which most organisms translate genetic material into protein metabolism, is non-
randomly organized. The Error Minimization hypothesis posits that natural selection produced a code that buffers
genomes against the impact of mutations. However, previous studies supporting this hypothesis treat the code
as an isolated trait, ignoring its influence on the evolution of the protein coding genome that it serves. A
population genetic model of molecular evolution was developed to test the rate of adaptive gene evolution under
different genetic codes. It is shown that the pattern of codon assignments has a profound effect on the speed
of adaptive evolution, and a fundamental re-interpretation of the adaptive genetic code is offered, from one
that minimizes errors to one that enhances the efficacy of natural selection. CIRC helped this work by
performing the extensive numerical simulations required.

*Additional outcomes:* This project led to a publication:

- Wen Zhu and Stephen Freeland.
The Standard Genetic Code Enhances Adaptive Evolution of Proteins.
Submitted.

Numerical Simulations of a Current Neural Network Model

*March 18, 2004 to May 10, 2004*

*Client:* Dr. Jonathan Bell, Department of Mathematics and Statistics, UMBC

*Consultant: * Zorayr Manukyan, Mathematics

*Description:*
A certain integro-differential equation provides a model describing electrical activity of neural net. A numerical
method for solving it was developed. The relationship between parameters in the model resulted in different types
of wave phenomena.

*This project was conducted as part of the consulting class Math/Stat 750 in Spring 2004 under the supervision
of facilitator Dr. Matthias K. Gobbert.*

Cluster Analysis for Compositional Data

*March 18, 2004 to May 10, 2004*

*Client:* Dr. Erle Ellis, Department of Geography and Environmental Systems, UMBC

*Consultant:* Ronny O. Vallejos, Statistics

*Description:*
Cluster analysis is a statistical technique of interest in many different fields for grouping data. This work
presented a clustering technique to deal with compositional data, i.e. data consisting of vectors in which
the components are proportions adding up to one. Various strategies for replacing zeros in the data were
discussed. To illustrate the method we presented the analysis of a data set from the Yangtze Plain region in
China.

*This project was conducted as part of the consulting class Math/Stat 750 in Spring 2004 under the supervision
of the facilitator Dr. Nagaraj K. Neerchal.*

Data Analysis for Concentration of Atrazine in Ground Water and Area of Influence

*March 18, 2004 to May 10, 2004*

*Client:* Earl Greene, U.S. Geological Survey, Baltimore, MD

*Consultants:* Justin Newcomer and Rupa Bhensdadia, Statistics

*Description:*
Atrazine (a pesticide) is used to control broadleaf and grassy weeds. The U.S. Environmental Protection Agency
has set some standards for maximum contaminant level of Atrazine in drinking water. It is assumed that the response
variable, concentration of Atrazine, can be predicted with logistic regression. The model was fit using various
explanatory variables, collected for sample units. Also, an analysis was done to find the area of influence for
the above stated study.

*This project was conducted as part of the consulting class Math/Stat 750 in Spring 2004 under the supervision
of facilitator Dr. Nagaraj K. Neerchal.*

Sensitivity Analysis for a Plague Model

*March 18, 2004 to May 10, 2004*

*Client:* Dr. Holly Gaff, Dynamics Technology, Inc., Arlington, VA

*Consultants:* Stephen Clark and Jonathan Desi, Mathematics

*Description:*
Plague is considered a prominent disease threat. In the past, outbreaks have affected large amounts of the
population. Today, the threat of plague being used as a biological warfare and terrorism agent is a realistic
possibility. Researchers have studied this topic and developed a mathematical model of differential equations
to understand how plague behaves. Sensitivity analysis on certain parameters in the model was performed to see
how the behavior is affected. This analysis will hopefully help researchers in this area better understand the
behavior of plague.

*This project was conducted as part of the consulting class Math/Stat 750 in Spring 2004 under the supervision
of facilitator Dr. Matthias K. Gobbert.*