
Search the School of Mathematical SciencesPeople matching "Gene expression studies"Events matching "Gene expression studies" 
Stability of timeperiodic flows 15:10 Fri 10 Mar, 2006 :: G08 Mathematics Building University of Adelaide :: Prof. Andrew Bassom, School of Mathematics and
Statistics, University of Western Australia
Timeperiodic shear layers occur naturally in a wide
range of applications from engineering to physiology. Transition to
turbulence in such flows is of practical interest and there have been
several papers dealing with the stability of flows composed of a
steady component plus an oscillatory part with zero mean. In such
flows a possible instability mechanism is associated with the mean
component so that the stability of the flow can be examined using some
sort of perturbationtype analysis. This strategy fails when the mean
part of the flow is small compared with the oscillatory component
which, of course, includes the case when the mean part is precisely
zero.
This difficulty with analytical studies has meant that the stability
of purely oscillatory flows has relied on various numerical
methods. Until very recently such techniques have only ever predicted
that the flow is stable, even though experiments suggest that they do
become unstable at high enough speeds. In this talk I shall expand on
this discrepancy with emphasis on the particular case of the socalled
flat Stokes layer. This flow, which is generated in a deep layer of
incompressible fluid lying above a flat plate which is oscillated in
its own plane, represents one of the few exact solutions of the
NavierStokes equations. We show theoretically that the flow does
become unstable to waves which propagate relative to the basic motion
although the theory predicts that this occurs much later than has been
found in experiments. Reasons for this discrepancy are examined by
reference to calculations for oscillatory flows in pipes and
channels. Finally, we propose some new experiments that might reduce
this disagreement between the theoretical predictions of instability
and practical realisations of breakdown in oscillatory flows. 

Watching evolution in real time; problems and potential research areas.
15:10 Fri 26 May, 2006 :: G08. Mathematics Building University of Adelaide :: Prof Alan Cooper (Federation Fellow)
Recent studies (1) have indicated problems with our
ability to use the genetic distances between species to estimate the
time since their divergence (so called molecular clocks). An
exponential decay curve has been detected in comparisons of closely
related taxa in mammal and bird groups, and rough approximations
suggest that molecular clock calculations may be problematic for the
recent past (eg <1 million years). Unfortunately, this period
encompasses a number of key evolutionary events where estimates of
timing are critical such as modern human evolutionary history, the
domestication of animals and plants, and most issues involved in
conservation biology. A solution (formulated at UA) will be briefly
outlined. A second area of active interest is the recent suggestion
(2) that mitochondrial DNA diversity does not track population size in
several groups, in contrast to standard thinking. This finding has
been interpreted as showing that mtDNA may not be evolving neutrally,
as has long been assumed.
Large ancient DNA datasets provide a means to examine these issues, by
revealing evolutionary processes in real time (3). The data also
provide a rich area for mathematical investigation as temporal
information provides information about several parameters that are
unknown in serial coalescent calculations (4). References: Ho SYW et al. Time dependency of molecular rate estimates and
systematic overestimation of recent divergence
times. Mol. Biol. Evol. 22, 15611568 (2005);
Penny D, Nature 436, 183184 (2005).
 Bazin E., et al. Population size does not influence mitochondrial
genetic diversity in animals. Science 312, 570 (2006);
EyreWalker A. Size does not matter for mitochondrial DNA,
Science 312, 537 (2006).
 Shapiro B, et al. Rise and fall of the Beringian steppe
bison. Science 306: 15611565 (2004);
Chan et al. Bayesian estimation of the timing and severity of a
population bottleneck from ancient DNA. PLoS Genetics, 2 e59
(2006).
 Drummond et al. Measurably evolving populations, Trends in
Ecol. Evol. 18, 481488 (2003);
Drummond et al. Bayesian coalescent inference of past population
dynamics from molecular sequences. Molecular Biology Evolution
22, 118592 (2005).


Modelling gene networks: the case of the quorum sensing network in bacteria. 15:10 Fri 1 Jun, 2007 :: G08 Mathematics Building University of Adelaide :: Dr Adrian Koerber
The quorum sensing regulatory genenetwork is employed by bacteria to provide a measure of their populationdensity and switch their behaviour accordingly. I will present an overview of quorum sensing in bacteria together with some of the modelling approaches I\'ve taken to describe this system. I will also discuss how this system relates to virulence and medical treatment, and the insights gained from the mathematics. 

Moderated Statistical Tests for Digital Gene Expression Technologies 15:10 Fri 19 Oct, 2007 :: G04 Napier Building University of Adelaide :: Dr Gordon Smyth :: Walter and Eliza Hall Institute of Medical Research in Melbourne, Australia
Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of DNA sequencing decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using overdispersed binomial or Poisson models for the counts, but none of the these are usable when the number of replicates is very small. We develop tests using the negative binomial distribution to model overdispersion relative to the Poisson, and use conditional weighted likelihood to moderate the level of overdispersion across genes. A heuristic empirical Bayes algorithm is developed which is applicable to very general likelihood estimation contexts. Not only is our strategy applicable even with the smallest number of replicates, but it also proves to be more powerful than previous strategies when more replicates are available. The methodology is applicable to other counting technologies, such as proteomic spectral counts.


The Role of Walls in Chaotic Mixing 15:10 Fri 22 Aug, 2008 :: G03 Napier Building University of Adelaide :: Dr JeanLuc Thiffeault :: Department of Mathematics, University of Wisconsin  Madison
I will report on experiments of chaotic mixing in closed and open
vessels, in which a highly viscous fluid is stirred by a moving
rod. In these experiments we analyze quantitatively how the
concentration field of a lowdiffusivity dye relaxes towards
homogeneity, and observe a slow algebraic decay, at odds with the
exponential decay predicted by most previous studies. Visual
observations reveal the dominant role of the vessel wall, which
strongly influences the concentration field in the entire domain and
causes the anomalous scaling. A simplified 1D model supports our
experimental results. Quantitative analysis of the concentration
pattern leads to scalings for the distributions and the variance of
the concentration field consistent with experimental and numerical
results. I also discuss possible ways of avoiding the limiting role
of walls.
This is joint work with Emmanuelle Gouillart, Olivier Dauchot, and
Stephane Roux. 

Boltzmann's Equations for Suspension Flow in Porous Media and Correction of the Classical Model 15:10 Fri 13 Mar, 2009 :: Napier LG29 :: Prof Pavel Bedrikovetsky :: University of Adelaide
Suspension/colloid transport in porous media is a basic phenomenon in environmental, petroleum and chemical engineering. Suspension of particles moves through porous media and particles are captured by straining or attraction. We revise the classical equations for particle mass balance and particle capture kinetics and show its nonrealistic behaviour in cases of large dispersion and of flowfree filtration. In order to resolve the paradoxes, the porescale model is derived. The model can be transformed to Boltzmann equation with particle distribution over pores. Introduction of sinksource terms into Boltzmann equation results in much more simple calculations if compared with the traditional ChapmanEnskog averaging procedure. Technique of projecting operators in Hilbert space of Fourier images is used. The projection subspace is constructed in a way to avoid dependency of averaged equations on sinksource terms. The averaging results in explicit expressions for particle flux and capture rate. The particle flux expression describes the effect of advective particle velocity decrease if compared with the carrier water velocity due to preferential capture of "slow" particles in small pores. The capture rate kinetics describes capture from either advective or diffusive fluxes. The equations derived exhibit positive advection velocity for any dispersion and particle capture in immobile fluid that resolves the abovementioned paradox.
Finally, we discuss validation of the model for propagation of contaminants in aquifers, for filtration, for potable water production by artesian wells, for formation damage in oilfields. 

Sloshing in tanks of liquefied natural gas (LNG) vessels 15:10 Wed 22 Apr, 2009 :: Napier LG29 :: Prof. Frederic Dias :: ENS, Cachan
The last scientific conversation I had with Ernie Tuck was on liquid impact. As a matter of fact, we discussed the paper by J.H. Milgram, Journal of Fluid Mechanics 37 (1969), entitled "The motion of a fluid in a cylindrical container with a free surface following vertical impact."
Liquid impact is a key issue in sloshing and in particular in sloshing in tanks of LNG vessels. Numerical simulations of sloshing have been performed by various groups, using various types of numerical methods. In terms of the numerical results, the outcome is often impressive, but the question remains of how relevant these results are when it comes to determining impact pressures. The numerical models are too simplified to reproduce the high variability of the measured pressures. In fact, for the time being, it is not possible to simulate accurately both global and local effects. Unfortunately it appears that local effects predominate over global effects when the behaviour of pressures is considered.
Having said this, it is important to point out that numerical studies can be quite useful to perform sensitivity analyses in idealized conditions such as a liquid mass falling under gravity on top of a horizontal wall and then spreading along the lateral sides. Simple analytical models inspired by numerical results on idealized problems can also be useful to predict trends.
The talk is organized as follows: After a brief introduction on the sloshing problem and on scaling laws, it will be explained to what extent numerical studies can be used to improve our understanding of impact pressures. Results on a liquid mass hitting a wall obtained by a finitevolume code with interface reconstruction as well as results obtained by a simple analytical model will be shown to reproduce the trends of experiments on sloshing.
This is joint work with L. Brosset (GazTransport & Technigaz), J.M. Ghidaglia (ENS Cachan) and J.P. Braeunig (INRIA). 

Nonlinear diffusiondriven flow in a stratified viscous fluid 15:00 Fri 26 Jun, 2009 :: Macbeth Lecture Theatre :: Associate Prof Michael Page :: Monash University
In 1970, two independent studies (by Wunsch and Phillips) of the behaviour of a linear densitystratified viscous fluid in a closed container demonstrated a slow flow can be generated simply due to the container having a sloping boundary surface This remarkable motion is generated as a result of the curvature of the lines of constant density near any sloping surface, which in turn enables a zero normalflux condition on the density to be satisfied along that boundary. When the Rayleigh number is large (or equivalently Wunsch's parameter $R$ is small) this motion is concentrated in the near vicinity of the sloping surface, in a thin `buoyancy layer' that has many similarities to an Ekman layer in a rotating fluid.
A number of studies have since considered the consequences of this type of `diffusivelydriven' flow in a semiinfinite domain, including in the deep ocean and with turbulent effects included. More recently, Page & Johnson (2008) described a steady linear theory for the broaderscale mass recirculation in a closed container and demonstrated that, unlike in previous studies, it is possible for the buoyancy layer to entrain fluid from that recirculation. That work has since been extended (Page & Johnson, 2009) to the nonlinear regime of the problem and some of the similarities to and differences from the linear case will be described in this talk. Simple and elegant analytical solutions in the limit as $R \to 0$ still exist in some situations, and they will be compared with numerical simulations in a tilted square container at small values of $R$. Further work on both the unsteady flow properties and the flow for other geometrical configurations will also be described. 

The Jeffery–Hamel similarity solution and its relation to flow in a diverging channel 15:10 Fri 19 Mar, 2010 :: Santos Lecture Theatre :: Dr Phil Haines :: University of Adelaide
Jeffery–Hamel flows describe the steady twodimensional flow of an
incompressible viscous fluid between plane walls separated by an angle
$\alpha$. They are often used to approximate the flow in domains of finite
radial extent. However, whilst the base Jeffery–Hamel solution is
characterised by a subcritical pitchfork bifurcation, studies in expanding
channels of finite length typically find symmetry breaking via a supercritical
bifurcation.
We use the finite element method to calculate solutions for flow in a
twodimensional wedge of finite length bounded by arcs of constant radii, $R_1$
and $R_2$. We present a comprehensive picture of the bifurcation structure and
nonlinear states for a net radial outflow of fluid. We find a series of nested
neutral curves in the Reynolds number$\alpha$ plane
corresponding to pitchfork bifurcations that break the midplane symmetry of the
flow. We show that these finite domain bifurcations remain distinct from the
similarity solution bifurcation even in the limit $R_2/R_1 \rightarrow \infty$.
We also discuss a class of stable steady solutions apparently related to a
steady, spatially periodic, wave first observed by Tutty (1996). These
solutions remain disconnected in our domain in the sense that they do not
arise via a local bifurcation of the Stokes flow solution as the Reynolds
number is increased. 

Estimation of sparse Bayesian networks using a scorebased approach 15:10 Fri 30 Apr, 2010 :: School Board Room :: Dr Jessica Kasza :: University of Copenhagen
The estimation of Bayesian networks given highdimensional data sets, with more variables than there are observations, has been the focus of much recent research. These structures provide a flexible framework for the representation of the conditional independence relationships of a set of variables, and can be particularly useful in the estimation of genetic regulatory networks given gene expression data.
In this talk, I will discuss some new research on learning sparse networks, that is, networks with many conditional independence restrictions, using a scorebased approach. In the case of genetic regulatory networks, such sparsity reflects the view that each gene is regulated by relatively few other genes. The presented approach allows prior information about the overall sparsity of the underlying structure to be included in the analysis, as well as the incorporation of prior knowledge about the connectivity of individual nodes within the network.


Whole genome analysis of repetitive DNA 15:10 Fri 21 May, 2010 :: Napier 209 :: Prof David Adelson :: University of Adelaide
The interspersed repeat content of mammalian genomes has been best characterized in human, mouse and cow. We carried out de novo identification of repeated elements in the equine genome and identified previously unknown elements present at low copy number. The equine genome contains typical eutherian mammal repeats. We analysed both interspersed and simple sequence repeats (SSR) genomewide, finding that some repeat classes are spatially correlated with each other as well as with G+C content and gene density. Based on these
spatial correlations, we have confirmed recentlydescribed ancestral vs cladespecific genome territories defined by repeat content. Territories enriched for ancestral repeats tended to be contiguous domains. To determine if these territories were evolutionarily conserved, we compared these results with a similar analysis of the human genome, and observed similar ancestral repeat enriched domains. These results indicate that ancestral, evolutionarily conserved mammalian genome territories can be identified on the basis of repeat content alone. Interspersed repeats of different ages appear to be analogous to geologic strata, allowing identification of ancient vs newly remodelled regions of mammalian genomes. 

Meteorological drivers of extreme bushfire events in southern Australia 15:10 Fri 2 Jul, 2010 :: Benham Lecture Theatre :: Prof Graham Mills :: Centre for Australian Weather and Climate Research, Melbourne
Bushfires occur regularly during summer in southern Australia, but only a few of these fires become iconic due to their effects, either in terms of loss of life or economic and social cost. Such events include Black Friday (1939), the Hobart fires (1967), Ash Wednesday (1983), the Canberra bushfires (2003), and most recently Black Saturday in February 2009. In most of these events the weather of the day was statistically extreme in terms of heat, (low) humidity, and wind speed, and in terms of antecedent drought. There are a number of reasons for conducting postevent analyses of the meteorology of these events. One is to identify any meteorological circulation systems or dynamic processes occurring on those days that might not be widely or hitherto recognised, to document these, and to develop new forecast or guidance products. The understanding and prediction of such features can be used in the short term to assist in effective management of fires and the safety of firefighters and in the medium range to assist preparedness for the onset of extreme conditions. The results of such studies can also be applied to simulations of future climates to assess the likely changes in frequency of the most extreme fire weather events, and their documentary records provide a resource that can be used for advanced training purposes. In addition, particularly for events further in the past, revisiting these events using reanalysis data sets and contemporary NWP models can also provide insights unavailable at the time of the events.
Over the past few years the Bushfire CRC's Fire Weather and Fire Danger project in CAWCR has studied the mesoscale meteorology of a number of major fire events, including the days of Ash Wednesday 1983, the Dandenong Ranges fire in January 1997, the Canberra fires and the Alpine breakout fires in January 2003, the Lower Eyre Peninsula fires in January 2005 and the Boorabbin fire in December 2007January 2008. Various aspects of these studies are described below, including the structures of dry cold frontal wind changes, the particular character of the cold fronts associated with the most damaging fires in southeastern Australia, and some aspects of how the vertical temperature and humidity structure of the atmosphere may affect the fire weather at the surface.
These studies reveal much about these major events, but also suggest future research directions, and some of these will be discussed.


A polyhedral model for boron nitride nanotubes 15:10 Fri 3 Sep, 2010 :: Napier G04 :: Dr Barry Cox :: University of Adelaide
The conventional rolledup model of nanotubes does not apply to the very small radii tubes, for which curvature effects become significant. In this talk an existing geometric model for carbon nanotubes proposed by the authors, which accommodates this deficiency and which is based on the exact polyhedral cylindrical structure, is extended to a nanotube structure involving two species of atoms in equal proportion, and in particular boron nitride nanotubes. This generalisation allows the principle features to be included as the fundamental assumptions of the model, such as equal bond length but distinct bond angles and radii between the two species. The polyhedral model is based on the five simple geometric assumptions: (i) all bonds are of equal length, (ii) all bond angles for the boron atoms are equal, (iii) all boron atoms lie at an equal distance from the nanotube axis, (iv) all nitrogen atoms lie at an equal distance from the nanotube axis, and (v) there exists a fixed ratio of pyramidal height H, between the boron species compared with the corresponding height in a symmetric single species nanotube.
Working from these postulates, expressions are derived for the various structural parameters such as radii and bond angles for the two species for specific values of the chiral vector numbers (n,m). The new model incorporates an additional constant of proportionality H, which we assume applies to all nanotubes comprising the same elements and is such that H = 1 for a single species nanotube. Comparison with `ab initio' studies suggest that this assumption is entirely reasonable, and in particular we determine the value H = 0.56\pm0.04 for boron nitride, based on computational results in the literature.
This talk relates to work which is a couple of years old and given time at the end we will discuss some newer results in geometric models developed with our former student Richard Lee (now also at the University of Adelaide as a post doc) and some workinprogress on carbon nanocones.
Note: pyramidal height is our own terminology and will be explained in the talk.


Explicit numerical simulation of multiphase and confined flows 15:10 Fri 8 Oct, 2010 :: Napier G04 :: Prof Mark Biggs :: University of Adelaide
Simulations in which the system of interest is essentially mimicked are termed explicit numerical simulations (ENS). Direct numerical simulation (DNS) of turbulence is a well known and longstanding example of ENS. Such simulations provide a basis for elucidating fundamentals in a way that is impossible experimentally and formulating and parameterizing engineering models with reduced experimentation. In this presentation, I will first outline the concept of ENS. I will then report a number of ENSbased studies of various multiphase fluid systems and flows in porous media. In the first of these studies, which is concerned with flow of suspensions in porous media accompanied by deposition, ENS is used to demonstrate the significant inadequacies of the classical trajectory models typically used for the study of such problems. In the second study, which is concerned with elucidating the change in binary droplet collision behaviour with Capillary number (Ca) and Reynolds number (Re), a range of collision scenarios are revealed as a function of Ca and Re and it appears that the boundaries between these scenarios in the CaRe space are not distinct but, rather, smeared. In the final study, it is shown that ENS an be used to predict ab initio the hydrodynamic properties of single phase flow through porous media from the Darcy to the turbulent regimes. 

Alignment of time course gene expression data sets using Hidden Markov Models 12:10 Mon 5 Sep, 2011 :: 5.57 Ingkarni Wardli :: Mr Sean Robinson :: University of Adelaide
Time course microarray experiments allow for insight into biological processes by measuring gene expression over a time period of interest. This project is concerned with time course data from a microarray experiment conducted on a particular variety of grapevine over the development of the grape berries at a number of different vineyards in South Australia. The aim of the project is to construct a methodology for combining the data from the different vineyards in order to obtain more precise estimates of the underlying behaviour of the genes over the development process. A major issue in doing so is that the rate of development of the grape berries is different at different vineyards.
Hidden Markov models (HMMs) are a well established methodology for modelling time series data in a number of domains and have been previously used for gene expression analysis. Modelling the grapevine data presents a unique modelling issue, namely the alignment of the expression profiles needed to combine the data from different vineyards. In this seminar, I will describe our problem, review HMMs, present an extension to HMMs and show some preliminary results modelling the grapevine data. 

Statistical modelling for some problems in bioinformatics 11:10 Fri 14 Oct, 2011 :: B.17 Ingkarni Wardli :: Professor Geoff McLachlan :: The University of Queensland
Media...In this talk we consider some statistical analyses of data arising in
bioinformatics. The problems include the detection of differential
expression in microarray geneexpression data, the clustering of
timecourse geneexpression data and, lastly, the analysis of
modernday cytometric data. Extensions are considered to the procedures
proposed for these three problems in McLachlan et al. (Bioinformatics, 2006),
Ng et al. (Bioinformatics, 2006), and Pyne et al. (PNAS, 2009), respectively.
The latter references are available at http://www.maths.uq.edu.au/~gjm/. 

Spatialpoint data sets and the Polya distribution 15:10 Fri 27 Apr, 2012 :: B.21 Ingkarni Wardli :: Dr Benjamin Binder :: The University of Adelaide
Media...Spatialpoint data sets, generated from a wide range of
physical systems and mathematical
models, can be analyzed by counting the number of objects in equally
sized bins. We find that the bin
counts are related to the Polya distribution. New indexes are
developed which quantify whether or not a
spatial data set is at its most evenly distributed state. Using three
case studies (Lagrangian fluid particles in chaotic laminar
flows, cellular automata agents in discrete models, and biological
cells within colonies),
we calculate the indexes and predict the spatialstate of the system. 

Multiscale models of collective cell behaviour: Linear or nonlinear diffusion? 15:10 Fri 4 May, 2012 :: B.21 Ingkarni Wardli :: Dr Matthew Simpson :: Queensland University of Technology
Media...Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. There is no guidance available in the mathematical biology literature with regard to which approach is more appropriate. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. We provide a link between individualbased and continuum models using a multiscale approach in which we analyse the collective motion of a population of interacting agents in a generalized latticebased exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description is a linear diffusion equation, whereas for elongated rodshaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is a nonlinear diffusion equation related to the porous media equation. We show that there are several reasonable approaches for dealing with agent size effects, and that these different approaches are related mathematically through the concept of mean action time. We extend our results to consider proliferation and travelling waves where greater care must be taken to ensure that the continuum model replicates the discrete process. This is joint work with Dr Ruth Baker (Oxford) and Dr Scott McCue (QUT). 

Adventures with group theory: counting and constructing polynomial invariants for applications in quantum entanglement and molecular phylogenetics 15:10 Fri 8 Jun, 2012 :: B.21 Ingkarni Wardli :: Dr Peter Jarvis :: The University of Tasmania
Media...In many modelling problems in mathematics and physics, a standard
challenge is dealing with several repeated instances of a system under
study. If linear transformations are involved, then the machinery of
tensor products steps in, and it is the job of group theory to control how
the relevant symmetries lift from a single system, to having many copies.
At the level of group characters, the construction which does this is
called PLETHYSM.
In this talk all this will be contextualised via two case studies:
entanglement invariants for multipartite quantum systems, and Markov
invariants for tree reconstruction in molecular phylogenetics. By the end
of the talk, listeners will have understood why Alice, Bob and Charlie
love Cayley's hyperdeterminant, and they will know why the three squangles
 polynomial beasts of degree 5 in 256 variables, with a modest 50,000
terms or so  can tell us a lot about quartet trees! 

Geometry  algebraic to arithmetic to absolute 15:10 Fri 3 Aug, 2012 :: B.21 Ingkarni Wardli :: Dr James Borger :: Australian National University
Media...Classical algebraic geometry is about studying solutions to systems of polynomial equations with complex coefficients. In arithmetic algebraic geometry, one digs deeper and studies the arithmetic properties of the solutions when the coefficients are rational, or even integral. From the usual point of view, it's impossible to go deeper than this for the simple reason that no smaller rings are available  the integers have no proper subrings. In this talk, I will explain how an emerging subject, lambdaalgebraic geometry, allows one to do just this and why one might care. 

Infectious diseases modelling: from biology to public health policy 15:10 Fri 24 Aug, 2012 :: B.20 Ingkarni Wardli :: Dr James McCaw :: The University of Melbourne
Media...The mathematical study of humantohuman transmissible pathogens has
established itself as a complementary methodology to the traditional
epidemiological approach. The classic susceptibleinfectiousrecovered
model paradigm has been used to great effect to gain insight into the
epidemiology of endemic diseases such as influenza and pertussis, and
the emergence of novel pathogens such as SARS and pandemic influenza.
The modelling paradigm has also been taken within the host and used to
explain the withinhost dynamics of viral (or bacterial or parasite)
infections, with implications for our understanding of infection,
emergence of drug resistance and optimal druginterventions.
In this presentation I will provide an overview of the mathematical
paradigm used to investigate both biological and epidemiological
infectious diseases systems, drawing on case studies from influenza,
malaria and pertussis research. I will conclude with a summary of how
infectious diseases modelling has assisted the Australian government in
developing its pandemic preparedness and response strategies.


Principal Component Analysis (PCA) 12:30 Mon 3 Sep, 2012 :: B.21 Ingkarni Wardli :: Mr Lyron Winderbaum :: University of Adelaide
Media...Principal Component Analysis (PCA) has become something of a buzzword recently in a number of disciplines including the gene expression and facial recognition. It is a classical, and fundamentally simple, concept that has been around since the early 1900's, its recent popularity largely due to the need for dimension reduction techniques in analyzing high dimensional data that has become more common in the last decade, and the availability of computing power to implement this. I will explain the concept, prove a result, and give a couple of examples. The talk should be accessible to all disciplines as it (should?) only assume first year linear algebra, the concept of a random variable, and covariance.


Interaction of doublestranded DNA inside singlewalled carbon nanotubes 12:10 Mon 5 Nov, 2012 :: B.21 Ingkarni Wardli :: Mr Mansoor Alshehri :: University of Adelaide
Media...Here we investigate the interaction of deoxyribonucleic acid (DNA) inside
single walled carbon nanotubes (SWCNTs). Using classical applied mathematical
modeling, we derive explicit analytical expressions for the encapsulation of
DNA inside singlewalled carbon nanotubes. We adopt the 612 LennardJones
potential function together with the continuous approach to determine the
preferred minimum energy position of the dsDNA molecule inside a singlewalled
carbon nanotube, so as to predict its location with reference to the cross
section of the carbon nanotube. An analytical expression is obtained in terms
of hypergeometric functions, which provides a computationally rapid procedure
to determine critical numerical values. 

Medical Decision Analysis 12:10 Mon 2 Sep, 2013 :: B.19 Ingkarni Wardli :: Eka Baker :: University of Adelaide
Doctors make life changing decisions every day based on clinical trial data. However, this data is often obtained from studies on healthy individuals or on patients with only the disease that a treatment is targeting. Outside of these studies, many patients will have other conditions that may affect the predicted benefit of receiving a certain treatment. I will talk about what clinical trials are, how to measure the benefit of treatments, and how having multiple conditions (comorbidities) will affect the benefit of treatments. 

Interaction of doublestranded DNA inside singlewalled carbon nanotubes 12:35 Mon 28 Oct, 2013 :: B.19 Ingkarni Wardli :: Mansoor Alshehri :: University of Adelaide
Media...Here we investigate the interaction of deoxyribonucleic acid (DNA) inside single walled carbon nanotubes (SWCNTs). Using classical applied mathematical modeling, we derive explicit analytical expressions for the encapsulation of DNA inside singlewalled carbon nanotubes. We adopt the 612 LennardJones potential function together with the continuous approach to determine the preferred minimum energy position of the dsDNA molecule inside a singlewalled carbon nanotube, so as to predict its location with reference to the cross section of the carbon nanotube. An analytical expression is obtained in terms of hypergeometric functions, which provides a computationally rapid procedure to determine critical numerical values. 

Networkbased approaches to classification and biomarker identification in metastatic melanoma 15:10 Fri 2 May, 2014 :: B.21 Ingkarni Wardli :: Associate Professor Jean Yee Hwa Yang :: The University of Sydney
Media...Finding prognostic markers has been a central question in much of current research in medicine and biology. In the last decade, approaches to prognostic prediction within a genomics setting are primarily based on changes in individual genes / protein. Very recently, however, network based approaches to prognostic prediction have begun to emerge which utilize interaction information between genes. This is based on the believe that largescale molecular interaction networks are dynamic in nature and changes in these networks, rather than changes in individual genes/proteins, are often drivers of complex diseases such as cancer.
In this talk, I use data from stage III melanoma patients provided by Prof. Mann from Melanoma Institute of Australia to discuss how network information can be utilize in the analysis of gene expression analysis to aid in biological interpretation. Here, we explore a number of novel and previously published networkbased prediction methods, which we will then compare to the common singlegene and geneset methods with the aim of identifying more biologically interpretable biomarkers in the form of networks. 

Hydrodynamics and rheology of selfpropelled colloids 15:10 Fri 8 Aug, 2014 :: B17 Ingkarni Wardli :: Dr Sarthok Sircar :: University of Adelaide
The subcellular world has many components in common with soft condensed matter systems (polymers, colloids and liquid crystals). But it has novel properties, not present in traditional complex fluids, arising from a rich spectrum of nonequilibrium behavior: flocking, chemotaxis and bioconvection.
The talk is divided into two parts. In the first half, we will (get an idea on how to) derive a hydrodynamic model for selfpropelled particles of an arbitrary shape from first principles, in a sufficiently dilute suspension limit, moving in a 3dimensional space inside a viscous solvent. The model is then restricted to particles with ellipsoidal geometry to quantify the interplay of the longrange excluded volume and the shortrange selfpropulsion effects. The expression for the constitutive stresses, relating the kinetic theory with the momentum transport equations, are derived using a combination of the virtual work principle (for extra elastic stresses) and symmetry arguments (for active stresses).
The second half of the talk will highlight on my current numerical expertise. In particular we will exploit a specific class of spectral basis functions together with RK4 timestepping to determine the dynamical phases/structures as well as phasetransitions of these ellipsoidal clusters. We will also discuss on how to define the order (or orientation) of these clusters and understand the other rheological quantities.


Software and protocol verification using Alloy 12:10 Mon 25 Aug, 2014 :: B.19 Ingkarni Wardli :: Dinesha Ranathunga :: University of Adelaide
Media...Reliable software isn't achieved by trial and error. It requires tools to support verification. Alloy is a tool based on set theory that allows expression of a logicbased model of software or a protocol, and hence allows checking of this model. In this talk, I will cover its key concepts, language syntax and analysis features. 

Testing Statistical Association between Genetic Pathways and Disease Susceptibility 12:10 Mon 1 Sep, 2014 :: B.19 Ingkarni Wardli :: Andy Pfieffer :: University of Adelaide
Media...A major research area is the identification of genetic pathways associated with various diseases. However, a detailed comparison of methods that have been designed to ascertain the association between pathways and diseases has not been performed.
I will give the necessary biological background behind GenomeWide Association Studies (GWAS), and explain the shortfalls in traditional GWAS methodologies. I will then explore various methods that use information about genetic pathways in GWAS, and explain the challenges in comparing these methods. 

Problems in pandemic preparedness 15:10 Fri 12 Sep, 2014 :: N132 Engineering North :: Dr Joshua Ross :: The University of Adelaide
Media...The emergence of novel strains of viruses pose an everpresent
threat to our health and wellbeing. In this talk, I will provide an
overview of work I have done, or am doing, in collaboration with
colleagues and students on two topics related to pandemic preparedness:
the first being antiviral usage for pre and postexposure prophylaxis;
and the second being estimating transmissibility and severity from First
Few Hundred (FF100) studies. 

Dynamics on Networks: The role of local dynamics and global networks on hypersynchronous neural activity 15:10 Fri 31 Jul, 2015 :: Ingkarni Wardli B21 :: Prof John Terry :: University of Exeter, UK
Media...Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of mathematical modelling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit.
In the talk we introduce some of these concepts with application to epilepsy, introducing a dynamic network approach to study resting state EEG recordings from a cohort of 35 people with epilepsy and 40 adult controls. Using this framework we demonstrate a strongly significant difference between networks inferred from the background activity of people with epilepsy in comparison to normal controls. Our findings demonstrate that a mathematical model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which may ultimately enable a more appropriate mechanistic stratification of people with epilepsy leading to improved diagnostics and therapeutics. 

Can Facebook Change your Mood? 12:10 Mon 28 Sep, 2015 :: Benham Labs G10 :: Tessa Longstaff :: University of Adelaide
Media...When studies are conducted on humans there are several ethical considerations that physicians must adhere to. Some people have argued that a recent study by Facebook has violated some of these ethical issues. In this talk I will introduce the ethics behind human clinical trials and then discuss a study conducted by Facebook, which considered emotional contagions on networks. The ethical considerations for this study will be explored and finally we can conclude if Facebook can change your mood. 

Modelling Coverage in RNA Sequencing 09:00 Mon 9 Nov, 2015 :: Ingkarni Wardli 5.57 :: Arndt von Haeseler :: Max F Perutz Laboratories, University of Vienna
Media...RNA sequencing (RNAseq) is the method of choice for measuring the expression of RNAs in a cell population. In an RNAseq experiment, sequencing the full length of larger RNA molecules requires fragmentation into smaller pieces to be compatible with limited read lengths of most deepsequencing technologies. Unfortunately, the issue of nonuniform coverage across a genomic feature has been a concern in RNAseq and is attributed to preferences for certain fragments in steps of library preparation and sequencing. However, the disparity between the observed nonuniformity of read coverage in RNAseq data and the assumption of expected uniformity elicits a query on the read coverage profile one should expect across a transcript, if there are no biases in the sequencing protocol. We propose a simple model of unbiased fragmentation where we find that the expected coverage profile is not uniform and, in fact, depends on the ratio of fragment length to transcript length. To compare the nonuniformity proposed by our model with experimental data, we extended this simple model to incorporate empirical attributes matching that of the sequenced transcript in an RNAseq experiment. In addition, we imposed an experimentally derived distribution on the frequency at which fragment lengths occur.
We used this model to compare our theoretical prediction with experimental data and with the uniform coverage model. If time permits, we will also discuss a potential application of our model. 

Use of epidemic models in optimal decision making 15:00 Thu 19 Nov, 2015 :: Ingkarni Wardli 5.57 :: Tim Kinyanjui :: School of Mathematics, The University of Manchester
Media...Epidemic models have proved useful in a number of applications in epidemiology. In this work, I will present two areas that we have used modelling to make informed decisions. Firstly, we have used an age structured mathematical model to describe the transmission of Respiratory Syncytial Virus in a developed country setting and to explore different vaccination strategies. We found that delayed infant vaccination has significant potential in reducing the number of hospitalisations in the most vulnerable group and that most of the reduction is due to indirect protection. It also suggests that marked public health benefit could be achieved through RSV vaccine delivered to age groups not seen as most at risk of severe disease. The second application is in the optimal design of studies aimed at collection of householdstratified infection data. A design decision involves making a tradeoff between the number of households to enrol and the sampling frequency. Two commonly used study designs are considered: crosssectional and cohort. The search for an optimal design uses Bayesian methods to explore the joint parameterdesign space combined with Shannon entropy of the posteriors to estimate the amount of information for each design. We found that for the crosssectional designs, the amount of information increases with the sampling intensity while the cohort design often exhibits a tradeoff between the number of households sampled and the intensity of followup. Our results broadly support the choices made in existing data collection studies. 

Approaches to modelling cells and remodelling biological tissues 14:10 Wed 10 Aug, 2016 :: Ingkarni Wardli 5.57 :: Professor Helen Byrne :: University of Oxford
Biological tissues are complex structures, whose evolution is characterised by multiple biophysical processes that act across diverse space and time scales. For example, during normal wound healing, fibroblast cells located around the wound margin exert contractile forces to close the wound while those located in the surrounding tissue synthesise new tissue in response to local growth factors and mechanical stress created by wound contraction. In this talk I will illustrate how mathematical modelling can provide insight into such complex processes, taking my inspiration from recent studies of cell migration, vasculogenesis and wound healing. 

Ktypes of tempered representations 12:10 Fri 7 Apr, 2017 :: Napier 209 :: Peter Hochs :: University of Adelaide
Media...Tempered representations of a reductive Lie group G are the irreducible unitary representations one needs in the Plancherel decomposition of L^2(G). They are relevant to harmonic analysis because of this, and also occur in the Langlands classification of the larger class of admissible representations. If K in G is a maximal compact subgroup, then there is a considerable amount of information in the restriction of a tempered representation to K. In joint work with Yanli Song and Shilin Yu, we give a geometric expression for the decomposition of such a restriction into irreducibles. The multiplicities of these irreducibles are expressed as indices of Dirac operators on reduced spaces of a coadjoint orbit of G corresponding to the representation. These reduced spaces are Spinc analogues of reduced spaces in symplectic geometry, defined in terms of moment maps that represent conserved quantities. This result involves a Spinc version of the quantisation commutes with reduction principle for noncompact manifolds. For discrete series representations, this was done by Paradan in 2003. 

Lagrangian transport in deterministic flows: from theory to experiment 16:10 Tue 16 May, 2017 :: Engineering North N132 :: Dr Michel Speetjens :: Eindhoven University of Technology
Transport of scalar quantities (e.g. chemical species, nutrients, heat) in deterministic flows is key to a wide range of phenomena and processes in industry and Nature. This encompasses length scales ranging from microns to hundreds of kilometres, and includes systems as diverse as viscous flows in the processing industry, microfluidic flows in labsonachip and porous media, largescale geophysical and environmental flows, physiological and biological flows and even continuum descriptions of granular flows.
Essential to the net transport of a scalar quantity is its advection by the fluid motion. The Lagrangian perspective (arguably) is the most natural way to investigate advection and leans on the fact that fluid trajectories are organized into coherent structures that geometrically determine the advective transport properties. Lagrangian transport is typically investigated via theoretical and computational studies and often concerns idealized flow situations that are difficult (or even impossible) to create in laboratory experiments. However, bridging the gap from theoretical and computational results to realistic flows is essential for their physical meaningfulness and practical relevance. This presentation highlights a number of fundamental Lagrangian transport phenomena and properties in both twodimensional and threedimensional flows and demonstrates their physical validity by way of representative and experimentally realizable flows. 

In space there is noone to hear you scream 12:10 Tue 12 Sep, 2017 :: Inkgarni Wardli 5.57 :: A/Prof Gary Glonek :: School of Mathematical Sciences
Media...Modern data problems often involve data in very high dimensions. For example, gene expression profiles, used to develop cancer screening models, typically have at least 30,000 dimensions. When dealing with such data, it is natural to apply intuition from low dimensional cases. For example, in a sample of normal observations, a typical data point will be near the centre of the distribution with only a small number of points at the edges.
In this talk, simple probability theory will be used to show that the geometry of data in high dimensional space is very different from what we can see in one and twodimensional examples. We will show that the typical data point is at the edge of the distribution, a long way from its centre and even further from any other points. 

Stochastic Modelling of Urban Structure 11:10 Mon 20 Nov, 2017 :: Engineering Nth N132 :: Mark Girolami :: Imperial College London, and The Alan Turing Institute
Media...Urban systems are complex in nature and comprise of a large number of individuals that act according to utility, a measure of net benefit pertaining to preferences. The actions of individuals give rise to an emergent behaviour, creating the socalled urban structure that we observe. In this talk, I develop a stochastic model of urban structure to formally account for uncertainty arising from the complex behaviour. We further use this stochastic model to infer the components of a utility function from observed urban structure. This is a more powerful modelling framework in comparison to the ubiquitous discrete choice models that are of limited use for complex systems, in which the overall preferences of individuals are difficult to ascertain. We model urban structure as a realization of a Boltzmann distribution that is the invariant distribution of a related stochastic differential equation (SDE) that describes the dynamics of the urban system. Our specification of Boltzmann distribution assigns higher probability to stable configurations, in the sense that consumer surplus (demand) is balanced with running costs (supply), as characterized by a potential function. We specify a Bayesian hierarchical model to infer the components of a utility function from observed structure. Our model is doublyintractable and poses significant computational challenges that we overcome using recent advances in Markov chain Monte Carlo (MCMC) methods. We demonstrate our methodology with case studies on the London retail system and airports in England. 

Calculating optimal limits for transacting credit card customers 15:10 Fri 2 Mar, 2018 :: Horace Lamb 1022 :: Prof Peter Taylor :: University of Melbourne
Credit card users can roughly be divided into `transactors', who pay off their balance each month, and `revolvers', who maintain an outstanding balance, on which they pay substantial interest.
In this talk, we focus on modelling the behaviour of an individual transactor customer. Our motivation is to calculate an optimal credit limit from the bank's point of view. This requires an expression for the expected outstanding balance at the end of a payment period.
We establish a connection with the classical newsvendor model. Furthermore, we derive the Laplace transform of the outstanding balance, assuming that purchases are made according to a marked point process and that there is a simplified balance control policy which prevents all purchases in the rest of the payment period when the credit limit is exceeded. We then use the newsvendor model and our modified model to calculate bounds on the optimal credit limit for the more realistic balance control policy that accepts all purchases that do not exceed the limit.
We illustrate our analysis using a compound Poisson process example and show that the optimal limit scales with the distribution of the purchasing process, while the probability of exceeding the optimal limit remains constant.
Finally, we apply our model to some real credit card purchase data. 

Models, machine learning, and robotics: understanding biological networks 15:10 Fri 16 Mar, 2018 :: Horace Lamb 1022 :: Prof Steve Oliver :: University of Cambridge
The availability of complete genome sequences has enabled the construction of computer models of metabolic networks that may be used to predict the impact of genetic mutations on growth and survival. Both logical and constraintbased models of the metabolic network of the model eukaryote, the ale yeast Saccharomyces cerevisiae, have been available for some time and are continually being improved by the research community. While such models are very successful at predicting the impact of deleting single genes, the prediction of the impact of higher order genetic interactions is a greater challenge. Initial studies of limited gene sets provided encouraging results. However, the availability of comprehensive experimental data for the interactions between genes involved in metabolism demonstrated that, while the models were able to predict the general properties of the genetic interaction network, their ability to predict interactions between specific pairs of metabolic genes was poor. I will examine the reasons for this poor performance and demonstrate ways of improving the accuracy of the models by exploiting the techniques of machine learning and robotics.
The utility of these metabolic models rests on the firm foundations of genome sequencing data. However, there are two major problems with these kinds of network models  there is no dynamics, and they do not deal with the uncertain and incomplete nature of much biological data. To deal with these problems, we have developed the Flexible Nets (FNs) modelling formalism. FNs were inspired by Petri Nets and can deal with missing or uncertain data, incorporate both dynamics and regulation, and also have the potential for model predictive control of biotechnological processes.


Projected Particle Filters 15:10 Fri 24 Aug, 2018 :: Lower Napier LG15 :: Dr John Maclean :: University of Adelaide
cientific advances owe equally to models and data, and both will remain relevant and key to further understanding. Observations drive model development, and model development often drives data acquisition. It therefore is particularly prudent to have these two sides of the scientific coin work in concert. This is a mathematical and statistical question: how to combine the output of model investigations and observational data. The area that is dedicated to studying and developing the best approaches to this issue is called Data Assimilation (DA). Perhaps the most crucial modernday application of DA is numerical weather prediction, but it is also used in GPS systems and studies of atmospheric conditions on other planets.
I will take the probabilistic or Bayesian approach to DA. At a particular time at which data are available, the question of data assimilation is how to approximate the posterior or analysis distribution, that is found by conditioning the "forecast distribution" on the data. A key method under this umbrella is the particle filter, that approximates the forecast and posterior distributions with an ensemble of weighted particles.
The talk will focus on a contribution to particle filtering made from a dynamical systems point of view. I will introduce a framework for Particle Filtering, PFAUS, in which only the components of data corresponding to the unstable and neutral modes of the forecast model are assimilated.
The particle filter is well suited to nonlinear forecast models, and nonGaussian forecast distributions, but would normally require exponentially more computational effort as the dimension of the DA problem increases. The PFAUS implementation is shown to correspond to assimilating observations of a lower dimension, equal to the number of Lyapunov exponents. The dimension of the observations is crucial in the computational cost of the particle filter and this approach is a framework to drastically lower that cost while preserving as much relevant information as possible, in that the unstable and neutral modes correspond to the most uncertain model predictions.
Particle filters are an active area of research in both the DA and the statistical communities, and there are many competing algorithms. One nice feature of PFAUS is that it is not exactly an algorithm but rather a framework for filtering: any particle filter can be applied in the PFAUS framework. 
News matching "Gene expression studies" 
Mini Winter School on Geometry and Physics The Institute for Geometry and its Applications will host a Winter School on Geometry and Physics on 2022 July 2009. There will be three days of expository lectures aimed at 3rd year and honours students interested in postgraduate studies in pure mathematics or mathematical physics. Posted Wed 24 Jun 09.More information... 
Publications matching "Gene expression studies"Publications 

EvidenceBased Medicine Evaluation of Electrophysiological Studies of the Anxiety Disorders Clark, C; Galletly, Cherrie; Ash, David; Moores, K; Penrose, R; McFarlane, Alexander, Clinical EEG and Neuroscience 40 (84–112) 2009  Evolving gene frequencies in a population with three possible alleles at a locus Hajek, Bronwyn; Broadbridge, P; Williams, G, Mathematical and Computer Modelling 47 (210–217) 2008  Gene profiling for determining pluripotent genes in a time course microarray experiment Tuke, Simon; Glonek, Garique; Solomon, Patricia, Biostatistics 10 (80–93) 2008  Gene expression analysis of multiple gastrointestinal regions reveals activation of common cell regulatory pathways following cytotoxic chemotherapy Bowen, Joanne; Gibson, Rachel; Tsykin, Anna; Stringer, Andrea Marie; Logan, Richard; Keefe, Dorothy, International Journal of Cancer 121 (1847–1856) 2007  Irinotecan changes gene expression in the small intestine of the rat with breast cancer Bowen, Joanne; Gibson, Rachel; Cummins, Adrian; Tyskin, A; Keefe, Dorothy, Cancer Chemotherapy and Pharmacology 59 (337–348) 2007  Microarray gene expression profiling of osteoarthritic bone suggests altered bone remodelling, WNT and transforming growth factorbeta/bone morphogenic protein signalling Hopwood, Blair; Tsykin, Anna; Findlay, David; Fazzalari, Nicola, Arthritis Research & Therapy 9 (WWW 1–WWW 21) 2007  Genetic regulators of myelopoiesis and leukemic signaling identified by gene profiling and linear modeling Brown, Anna; Wilkinson, Christopher; Waterman, S; Kok, Chung; Salerno, Diana; Diakiw, Sonya; Reynolds, Brenton; Scott, Hamish; Tsykin, Anna; Glonek, Garique; Goodall, Gregory; Solomon, Patricia; Gonda, Thomas; D'Andrea, Richard, Journal of Leukocyte Biology 80 (433–447) 2006  Numerical studies on the approximation of horizontal diffusion using sigma coordinate system Lee, Jong; Teubner, Michael; Nixon, John; Cho, YS, KSCE Journal of Civil Engineering 10 (145–149) 2006  Expression profiling reveals functionally important genes and coordinately regulated signaling pathway genes during in vitro angiogenesis Hahn, Christopher; Su, Zhi; Drogemuller, C; Tsykin, Anna; Waterman, S; Brautigan, P; Yu, S; Kremmidiotis, Gabriel; Gardner, A; Solomon, Patricia; Goodall, Gregory; Vadas, Matthew Alexander; Gamble, Jennifer, Physiological Genomics 22 (57–69) 2005  Selfsimilar "stagnation point" boundary layer flows with suction or injection King, J; Cox, Stephen, Studies in Applied Mathematics 115 (73–107) 2005  Expression profiling of a myeloid cell line model to identify novel transcription factors influencing myeloid cell differentiation, proliferation and leukaemia Wilkinson, Christopher; Brown, Anna; Kok, Chung; Solomon, Patricia; Goodall, Gregory; Gonda, Thomas; D'Andrea, M, 5th Australian Microarray Conference 2005, Barossa Valley, South Australia 29/09/05  Expression profiling of lineagespecific differentiation of pluripotent embyronic stem cells Wilkinson, Christopher; Keough, Rebecca; Harvey, Nathan; Lonic, Ana; Solomon, Patricia; Rathjen, Peter; Rathjen, Joy, 5th Australian Microarray Conference 2005, Barossa Valley, South Australia 29/09/05  Optimal designs for gene expression studies Sanchez, Penny Susan; Glonek, Garique; Solomon, Patricia, Twentieth International Workshop on Statistical Modelling, Sydney, Sydney, Australia 10/07/05  The interpretation of uncontrolled beforeandafter studies: As demonstrated by recent studies of the introduction of medical emergency teams Moran, John; Solomon, Patricia, Critical care and Resuscitation 7 (153–159) 2005  LargeReynoldsnumber asymptotics of the Berman problem Cox, Stephen; King, J, Studies in Applied Mathematics 113 (217–243) 2004  The nonparallel evolution of nonlinear short waves in buoyant boundary layers Denier, James; Bassom, A, Studies in Applied Mathematics 110 (139–156) 2003  Misclassification, correlation, and cause of death studies Tallis, George, Human Biology 74 (75–81) 2002  On Boutroux's tritronque solutions of the first Painlev equation Joshi, Nalini; Kitaev, Alexandre, Studies in Applied Mathematics 107 (253–291) 2001  Nonexistence results for the Kortewegde Vries and KadomtsevPetviashvili equations Joshi, Nalini; Petersen, J; Schubert, Luke Mark, Studies in Applied Mathematics 105 (361–374) 2000  Disease surveillance and intervention studies in developing countries Solomon, Patricia, Statistical Methods in Medical Research 9 (183–184) 2000 
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