D. Brian Walton
Assistant Professor
Department of Mathematics and Statistics
James Madison University
Address:
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James Madison University
Department of Mathematics
MSC 1911
Harrisonburg VA 22807
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Office:
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Roop 110
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| Hours: |
M 1-3 pm, T 11:30-1:30 pm, and W 1-2 pm or by
appointment |
Phone:
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(540) 568-6387
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Fax:
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(540) 568-6857
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E-Mail:
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waltondb@jmu.edu |
Quick Links
Here is a link to a PDF file containing the slides from my talk at JMM08:
Biological Applications Illustrating Linear
Algebra Concepts.
Here is a link to a PDF file to create a simple circular slide rule: Circular Slide Rule.
Here is a Java applet that finds all possible integer-valued solutions to
the 24 Game: 24 Game Solver.
Current JMU Courses (Spring 2008): Course information is on Blackboard.
- Math 318: Introduction to Probability and Statistics,
Section 2
Previous JMU Courses
- Fall 2007
- Math 238: Linear Algebra and Differential
Equations, Sections 1 and 2
- Spring 2007
- Math 236: Calculus II, Section 2
- Math 341/Physics 341: Non-Linear Dynamics and Chaos
- Fall 2006
- Math 235: Calculus 1 (2 sections)
- Math 342E/Biology 426: Mathematical Models in Biology
- Summer 2006
- Spring 2006
- Math 232: Calculus with Functions, Part 2
- Math 342E/Biology 325: Mathematical Models in Biology
- Fall 2005
- Math 231: Calculus with Functions, Part 1
- Math 248: Computers and Algorithms
- Summer 2005
- Math 231: Calculus with Functions, Part 1
- Spring 2005
- Math 232: Calculus with Functions, Part 2
- Fall 2004
- Math
231: Calculus with Functions, Part 1
Research Interests:
Recent rapid advances in quantitative biology lead to the need for
mathematically founded methods in analyzing these data and for models
that predict behaviors. I am particularly interested in developing
probabilistic models for experimental systems typically classified as
biophysics, and more particularly, experiments relating to motor
proteins. Such systems are fundamentally noisy because of thermal
fluctuations, so that stochastic processes arise naturally in studying
their behaviors.
One such motor protein, kinesin, is responsible for transporting
essential cellular products that are stored in membrane-bound vesicles
to distant regions of a cell. To do this, kinesin attaches to a
microtubule and essentially walks along its lattice. Recent experiments
allow biophysicists to track the progress of individual kinesin
proteins as they walk along a microtubule by observing an attached
microscopic sphere. I have developed a hidden Markov model filter for
analyzing data coming from such experiments, working with biophysicist
Koen Visscher to understand the biology and physics of the experiment
properly.
- Dissertation: "Analysis of Single-Molecule Kinesin Assay Data by
Hidden Markov Model Filtering," The University of Arizona, 2002. (PDF
version)
Recently, I have begun considering another protein related to kinesin
which is called mitotic centromere-associated kinesin (MCAK). Instead
of transporting cargo along a microtubule, MCAK finds the ends of the
microtubule and then proceeds to disassemble the microtubule. I am
particularly interested in modeling how this protein reaches the
microtubule ends and then how it contributes to the depolymerization of
the microtubule.
Of course, other topics catch my attention. Working with Koen Visscher,
I explored a topic referred to as "Noise Suppression by Noise" (Vilar
and Rubi, Phys. Rev. Lett. 86, 950 (2001)). This has been typically
regarded as an unintuitive phenomenon. Essentially, imagine an
input/output device where the output is a function of the input but
with additional noise, and where the size of the noise depends on the
particular value of the input. Noise suppression says that the size of
noise at the output can be reduced by increasing the fluctuations at
the input. We demonstrated that noise suppression simply corresponds to
spending a sufficiently large fraction of the time in low-noise input
states that the average size of noise is reduced. More precisely, we
explicitly compute the power spectrum of the output signal and provide
exact conditions for a decrease in the spectrum.
- D. Brian Walton and Koen Visscher, "Noise Suppression and
Spectral Decomposition for State-Dependent Noise in the Presence of a
Stationary Fluctuating Input", submitted 2003 (PDF
preprint)
Teaching Duties:
Prior to coming to James Madison University, I was a postdoctoral
research fellow at the University of Washington. In the Department
of Applied Mathematics, I taught a course titled "An
Introduction to Continuous Modeling" in the Department of Applied
Mathematics three times (Fall 2002, Spring 2003, and Fall 2003). This
class uses case studies in modeling with differential equations to
teach junior-level mathematical sciences students techniques in
developing and analyzing differential equations for various systems.
When I have taught this course, I have focused on population models,
competition models, predator-prey models, Lanchester combat models,
physical models with a potential energy, and traffic flow. This is a
fun course to teach, and students are introduced to a variety of tools
developed for dynamical systems such as bifurcations, phase-plane
analysis, linear stability of equilibria, and dimensional analysis.
This course also involves students preparing and writing a term project
applying differential equations to a model system of their choice. I
also taught one quarter of an Introduction to Numerical Methods.
Prior to coming to the UW, I taught three courses at the University of
Arizona in the Math department. I taught the series for College Algebra
(Math 116 and 117 at the time) as well as the introductory calculus
course Elements of Calculus (Math 113). I also was an advanced TA for
the graduate course in probability (Math 565), helping other graduate
students in problem sessions.
Off-Topic Links
If you are interested in my life philosophy
or hobbies, you might want
to visit my personal web page.
This web-page was written by D. Brian Walton.