NATIONAL UNIVERSITY OF IRELAND GALWAY

SCHOOL OF MATHEMATICS, STATISTICS AND APPLIED MATHEMATICS



Research day 2014

Research Presentations

Some mathematical models for drug delivery

Martin Meere

School of Mathematics, Statistics and Applied Mathematics

Drug-eluting stents are now commonly used in the treatment of coronary artery disease. These devices increase the flow of blood through blocked arteries and provide mechanical support to the artery wall. They also protect the artery from re-blockage due to inflammation by releasing an anti-inflammatory drug into the surrounding tissue from a polymer that coats the stent. However, the permanent presence of a polymer in the body is  now thought to increase the likelihood of a dangerous blood clot forming on thestent. Consequently, a new generation of stents are being developed that do not rely on a polymer to release the drug.

In these polymer-free stents, the drug is either sprayed directly onto a bare metal surface or infused in a metallic porous medium. Polymer free stents are a relatively new technology and no mathematical models have yet been developed to describe drug release from them. In this talk, some preliminary ideas for the modelling of polymer free stents are presented. The proposed models are based principally on dissolution theory and the theory of diffusion in porous media.

Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course
gene expression data

Emma Holian, Norma Coffey and John Hinde

School of Mathematics, Statistics and Applied Mathematics

Time-course microarray analyses involve measuring the expression levels of thousands of genes repeatedly through time. Multivariate clustering methods such as principal components analysis, k-means clustering, finite mixture models etc.\\ have difficulties handling missing values, require uniform sampling for all genes, fail to account for the correlation between measurements made on the same gene or do not facilitate the removal of noise from the measured data thus ignoring any smoothness that may be evident in the expression profiles. This talk proposes the use of curve-based clustering, which can handle the latter issues. We use the linear
mixed effects model representation of penalized spline smoothing to estimate the gene expression curves which provides a framework for simultaneously determining a smooth estimate of the mean expression profile in each cluster, determining estimates of the gene-specific expression profiles within a cluster through the use of additional random effects and clustering expression profiles using mixtures of mixed effects models.\\

Coffey, N., J. Hinde, and E. Holian. ``Clustering longitudinal profiles using P-splines and mixed effects models applied to time-course gene expression data.'' Computational Statistics & Data Analysis 71 (2014): 14-29.

DNA variation in a pathogen outbreak: past, present and predictions

Tim Downing

School of Mathematics, Statistics and Applied Mathematics

Mixing between genetically distinct pathogens within a population leads to novel combinations with altered host virulence and drug resistance. Such unique specimens represent either undiscovered lineages or re-assortments between established groups: comparison with known DNA patterns (haplotypes) provides a framework for determining ancestry and predicting biological traits. Current methods of allele frequency correlation, variant distribution modality and admixture modelling are effective for breeding between sub-species, but are untested for monomorphic populationswhere discriminatory mutations are rare. Haplotype distribution, size and length provided sufficient power to distinguish samples with just 3.4 mean pairwise SNPs/Mb in a sample of 191 Indian subcontinent clinical isolates of Leishmania donovani sampled in 2002-11 during two drug treatment eras. Model-based population clustering identified six genetically homogeneous populations with little evidence of recent interbreeding. These originated in the 1850s and showed a genetic bottleneck-recovery signature from anti-parasite pesticide spraying campaigns ending in the 1960s. Population-free membership assignment, phylogenetic trees and admixture statistics indicated six recent isolates were discovered whose haplotypes were mixes of these populations, despite as few as 60 genome-wide polymorphisms differentiating the main groups. These six hybrids were distinguishable from seven rare lineages
whose haplotype structure did not resemble any previous sample. Predicting resistance to future second-line or combination drug therapies using genetic data is now a tangible goal.

Categorising properties of road systems

Jorge Bruno, Aisling McCluskey

School of Mathematics, Statistics and Applied Mathematics

A road system on a nonempty set X is a family R of nonempty subsets of X such that:
  1. a is in R for all a in X,
  2. for all a, b in X, there is R in R such that a, b in R.
Each road system (X, R) gives rise to an R-relation R on X as follows:  [a,b,c]R holds if each road R containing a and c also contains b.
We explore some properties that are characteristic of R-relations using a categorical framework.

circular designs balanced for neighbours at distances one and two

Rosemary A. Bailey

University of St. Andrews, Scotland

TBA