Biomath Seminar
Fall 2010
Seminar meets W 3:35 in room 200 LOV. Syllabus
for the course.
Seminar schedule
- Aug. 25 no Wed. seminar, go to Friday colloquium of
Nick
Cogan
Speaker: Nick Cogan
Title: Modeling
Biofilm Processes, From Mathematics to Biology
Affiliation: Florida State University
Date: Friday, August 27, 2010
Place and Time: Room 101, Love Building, 3:35-4:30 pm
Refreshments: Room 204, Love Building, 3:00 pm
It is becoming more evident that bacteria outside of the lab
setting tend to live is structured communites termed biofilms. This
mode of existence is charactarized by aggragates of bacteria enmeshed
in a self-produced polymer matrix and imposes constraints on the how
the bacteria move, reproduce and react to disinfection external fluid
flow. This talk will review the analysis of a sequence of models that
explore the impact of these constraints on the bacterial dynamics.
- Sept.
1 Jonathan Bates, Scale-Space Spectral
Representation of Shape
First, we construct a space of representations of shape. In this
space, a shape is represented by functions of its intrinsic geometry
and the characterization of heat flow on the shape. This
representation is called a heat-kernel representation. Second, we
equip this space with metrics that derive from spectral representations
and the Hausdorff distance. Third, the computational challenge in this
shape distance is a minimization problem, which we approach with the
Markov chain Monte Carlo algorithm. Fourth, applications are
discussed.
- Sept. 8 Margaret Watts, Mechanisms for
Full-Length Resets in Pancreatic Islets
Bursting oscillations are common in neurons and endocrine cells. One
type of bursting model with two slow variables has been called "phantom
bursting" since the burst period is a blend of the time constants of
the slow variables. We describe a measure, which we call the "dominance
factor", of the relative contributions of the two slow variables to the
bursting produced by a simple phantom bursting model. Using this tool,
we demonstrate how the control of different phases of the burst can be
shifted from one slow variable to another by changing a model
parameter. We then show that the dominance curves obtained as a
parameter is varied can be useful in making predictions about the
resetting properties of the model cells. We provide experimental data
which shows that phase-independent resetting of a burst can be achieved
in the electrical activity of pancreatic islets. We demonstrate two
mechanisms by which this resetting can be achieved.
- Sept 15 Debbie
Striegel,
Animal Gaits and Symmetry
Patterns arise throughout nature. There are many techniques to
better understand biological patterning. Here, the
spatio-temporal patterns observed in animal gaits will be
reviewed. There are two approaches that are taken. First, a
coupled cell system will be used to model patterns
observed. Second, group theory will be used to show the
possible set of solutions and to give insight to the creation of the
patterns observed. Possible applications to cilia will also be
discussed.
- Sept 22
Sevgi Sengul, Discrete Fractional
Calculus and its Applicatioin to Tumor Growth
Almost every theory of mathematics has its discrete counterpart that
makes it conceptually easier to understand and practically easier to
use in the modeling process of real word problems. For instance, one
can calculate the "difference" of any function, from 1st order up to
the n-th order with some techniques in discrete calculus. However, it
is also possible to extend this calculation by means of discrete
fractional calculus and consider n any real number such that the
½-th order difference is well defined. In this talk, I
demonstrate some basic definitions and properties of discrete
fractional calculus while developing the simplest discrete fractional
variational theory and the related Euler-Lagrange equation. Also, I
will give a proof for Leibniz formula and state and prove the summation
by parts formula in discrete fractional calculus. The fractional
Gompertz difference equation (FGΔE) will be introduced. I will prove
the existence and uniqueness of the solution of (FGΔE) with an initial
condition. Then the (FGΔE) will be solved by the method of successive
approximation. Finally, some applications will be presented for tumor
growth and bacteria growth by use of real data.
- Sept 29 Gregory Toole, Growing Domain Turing
Systems & Cortical Folding
Little is understood about how the folds of the brain's
cerebral cortex form and why they are located where they are. One way
to investigate cortical folding is by developing a spatio-temporal
mathematical model of cortical folding using a Turing
reaction-diffusion system on an exponentially growing prolate
spheroidal domain. Such a model could be used to make predictions of
cortical folding patterns across species and account for cortical
folding variability within individuals of a species. In this
presentation, I will discuss the growing domain Turing system derived
in The effect of growth and
curvature on pattern formation (Plaza et al. 2004) and the
application of this system to an exponentially growing spherical domain
as discussed in Turing patterns on
growing spheres: the exponential case (Gjorgjieva and Jacobsen,
2007).
- Oct. 6 Faculty Showcase
- Oct 13 Arij Daou, From Birdsongs to
Neural Synapses and Mathematical Modeling
Sequences of motor activity are fundamental elements of animal and
human behavior. One of the touchstone questions in neuroscience is how
the brain learns and generates these complex sequences; this question
entails understanding of the underlying complex neural circuitry
responsible for producing these patterns. Like humans, songbirds learn
to produce highly stereotyped complex sequences of vocal gestures;
their songs. This renders the songbird an excellent model system for
studying sequential behavior and complex learned patterns. The learned
song pattern is generated by the HVC, a telencephalic nucleus that is
analogous to pre-motor cortical regions in mammals. The HVC contains
three neural populations: neurons that project to the telencephalic
motor output for song (RA), neurons that project to the avian striatum
(Area X), and interneurons. These three populations are interconnected,
with specific patterns of excitatory and inhibitory connectivity. We
have developed a simple ionic current-based computational model that
replicates this neural architecture, with the goal of understanding the
mechanism for the rhythmic firing patterns that occur in all three
neural populations during singing. Specifically, extracellular
recordings show that during singing HVC neurons that project to RA
produce ~10ms bursts that are time-locked to a specific temporal
position within the song pattern. In contrast, HVC neurons that project
to Area X spike or burst a few times and HVC interneurons spike or
burst densely throughout the song pattern. The mathematical model
reproduces these patterns, and shows how the sequence of activity can
be stored and directed by the specific excitatory and inhibitory
connections between these three types of neurons within the HVC
microcircuit. We discuss the elements of the model and the assumptions
that are required to produce the appropriate rhythmic behaviors.
- Oct 15 Friday:
colloquium James A Moorer, Mathematics Goes to
Hollywood
In the last two decades, all parts of
the modern audio and video production have moved to digital
computer-based equipment. As a result, technicians in Hollywood no
longer obsess over film dye lots and camera transport mechanisms, but
are just as likely these days to be found discussing the virtue of
dual-quaternion basis functions for smooth character animation.
This talk will illustrate the invasion of mathematics into the creative
process by taking a few concrete examples. I will try to show the
remarkable diversity of mathematical disciplines that are employed.
While the techniques can generally be described as applied mathematics,
they sometimes reveal some thorny theoretical issues as well.
- Oct. 27 Prof. Qing-Xiang (Amy)
Sang (FSU Chemistry) Macromolecular
Modulators in Cancer, Stroke, and Stem Cell Research
Cardiovascular diseases, cancer, and stroke are major killers of
Americans. Identification of biochemical pathways and molecular
mechanisms of disease initiation and progression is a major challenge
for biochemical and biomedical researchers. For the success of future
personalized medicine, scientists, mathematicians, and clinicians must
understand factors and biomarkers that are involved in the pathogenesis
of the disease. Matrix metalloproteinases (MMPs) are a family of
hydrolytic enzymes that require zinc for catalysis and calcium for
protein folding and stability. They are able to cleave extra cellular
matrix (ECM), pericellular and cell surface proteins such as growth
factors and signal receptors. MMPs are macromolecular modulators in
tissue 3-D re-structuring, remodeling, embryonic development,
morphogenesis, wound healing, and inflammation, and pathologies related
to cancer invasion, angiogenesis, and metastasis, as well as stroke,
atherosclerosis, and restenosis.
We and others have cloned, discovered, and biochemically characterized
human endometase/matrilysin-2/matrix metalloproteinase-26 (MMP-26)
using molecular biology, enzymology and medicinal chemistry approaches.
We have identified MMP-26 as a novel putative biomarker for preinvasive
stage of human breast and prostate cancer tissues. MMP-26 gene
and protein expression levels are very low in normal and benign human
tissues but the gene is turn on and the protein is highly expressed in
many different human carcinoma cells and tissues. MMP-26 might be
involved in the progression from an in situ tumor to an invasive
cancer. The complex role of MMP-26 in human cancer invasion and
progression remains to be further investigated. In collaboration with
Drs. Martin A. Schwartz and Yonghao Jin we have designed, synthesized,
and tested more than 300 novel MMP inhibitors and used them to
investigate the MMP structure and function relationship in biochemical
and cellular systems. The potential applications of MMP inhibitors in
cancer and cardiovascular disease, stroke, and stem cell research will
be discussed. Some problems in cancer, stroke, and stem cell research
that mathematicians may help to solve will also be presented.
(Supported by NIH, DOD CDMRP Prostate and Breast Cancer Research
Programs, Susan G. Komen Breast Cancer Foundation, Florida Breast
Cancer Research Coalition Foundation, Elsa U. Pardee Foundation, and
the Florida State University)
- Nov.
3 Rafael Martinez-Vega, Is the inability of
hearing the shape of drums enough to be no way able to trace out the
shape of objects?
The 1966 paper "Can one hear the shape of a drum?" by Mark Kac brought
up a rather interesting question regarding if the shape of an object
can be partially determined by its sound or the sound that it makes
(musicians must know
something of this by heart!) and its response in 1992 "One cannot hear
the shape of a drum" by Gordon, et al... arises interesting
modifications to the original question. Rather than just analyzing the
Wave Equation, the research done on the Heat Equation has come with
rather interesting results that address this topic. A bit about this
will be discussed briefly, focusing more on the facts that can be used
from its partial responses to the original question as practical tools
for image recognition needed for several issues in medical sciences.
The use of diverse analytical mathematical tools for surface
registration will be described.
- Nov.
10 Matt Donahue Modeling the
Interaction Between Fluid Flow in Plant Xylem and Biofilm Formation by
Xylella Fastidiosa in Pierce's Disease
There has been a recent explosion of interest in biofilm
infections due to the prevalence of the biofilm mode of life as well as
the inability to fully eliminate the bacteria within the biofilm.
Significant discoveries in biofilm formation involve advances in the
understanding of quorum sensing and biofilm "genes". However there has
been little attention paid to the formation and development of biofilm
diseases in plants; specifically Pierce's Disease which affect grape
vines, citrus plants, and some fruit trees. This bacterial infection
greatly reduces the amount and quality of produce before eventually
killing the plant itself. After a primer on the formation of biofilms
and the subsequent complications including the formation of Pierce's
Disease, a modeling framework will be proposed using multiphase
physics. An investigation of the system will follow featuring
linearization and perturbation analysis.
- Nov. 17 Raghu Kanumalla Simple Models of the
Heart, Circulation, and Cardiovascular Diseases
With heart disease and other cardiovascular anomalies threatening the
lives of more and more people, understanding this vital organ and its
related structures is crucial in the theory and practice of
Medicine. Early models of the heart and circulation were
formulated by Peskin using simple ideas from electric circuit theory,
differential equations and related numerical discretization
techniques.
Using Peskin's work as a starting point, one can expand them to
understand cardiovascular diseases. One notable disease is
Dilated Cardiomyopathy (DCM), which results in weakened cardiac muscle
that is unable to efficiently pump blood. This disease affects
many people as a result of congenital defects, drug and alcohol abuse,
or as a result of illness or other diseases.
Further research using these simple models can be applied to the
interaction of the cardiovascular system with other organs such as the
lungs and kidneys, and even further to fluid flow problems in
obstructed arteries.
- Nov. 24
no seminar
- Dec. 1 Prof. Edward
Bernat (FSU
Psychology) Time-frequency
approaches to disentangling brain processes associated with cognition,
emotion, and impulse dysregulation psychopathology.
Electroencephalographic (EEG)
event-related potential (ERP) measures have attracted renewed interest
in recent years. This is due to several factors. First,
evidence now indicates that EEG and functional magnetic resonance
imaging (fMRI) both index local field potential activity, EEG with
greater time resolution and fMRI with greater spatial resolution.
Second, developments in source localization models now offer reasonable
approaches to inferring neural sources underlying observed EEG/ERP
activity. Finally, new methods, including time-frequency (TF)
analysis, now offer stronger approaches to disentangling neural
activity that overlaps in time but not frequency. The presented
work utilizes these advances to better delineate cognitive and
emotional processes generally, and to assess for disruptions in these
processes related to impulse dysregulation (ID) psychopathology.
For example, reductions in the amplitude of the P300 ERP component are
perhaps the most widely studied neurophysiological indicator of impulse
dysregulation. Unfortunately, standard time-domain measures have
not produced useful decompositions of this activity to make clear
inferences about disruptions in underlying cognitive, emotional, or
neurophysiological processes. P300 and related data will be
presented from both community and incarcerated offender samples that
vary in ID. These analyses will show how multiple processes
concomitant with P300 can be disentangled using TF approaches,
providing a clearer assessment of ID-related activity.