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Advanced Research Computing Centre for Complex Systems Modelling

Research

Research Overview 

Our research spans computing, science, engineering and physics. We have had engagements with DCU colleagues and stakeholders in the following areas

  • Bioinformatics/Aging/Systems Biology
  • Secure and efficient Business
  • Environmental
  • Econometric/Financial Analysis
  • Open Source HPC Software Development  

 

  Time Series Analysis

 

Research Theme: Time Series Analysis

Time series of various forms are prevalent in our everyday lives, for instance arising from the monitoring of industrial processes or the tracking of corporate business metrics.  A key factor behind Time Series Analysis is that it accounts for the fact that the series contains data points which are taken over a period of time.  As a result the series may be noisy or contain bad data (that must be cleaned) it may have an internal structure (e.g. characteristic frequencies or trends) that must be accounted for, if there are multiple time series they may be correlated etc.  The data that has been analysed at the Centre has come from a variety of sources: finance; gene sequence; lifelog images .  All these are examined to try to tease out the information underpinning the data.

Group members                                  Position                

Dr. Martin Crane                                  Director, ARC-SYM Research Centre

Prof. Heather J. Ruskin                        Deputy Director, ARC-SYM

Marija Bezbradica                                Area Leader, ARC-SYM

See popular press article on time series analysis on twitter feeds here

What’s the big idea?

Typically time series come from making observations made over a certain time interval. There are a number of use-cases that could be involved: the whole science of climate change involves taking measurements (of pressure, temperature) from specific measuring stations over long time periods; time series are also used by coaching staff to get real-time feedback on players (and hence make better decisions based on up-to-date information) during a game. The main idea behind time series analysis is to use a certain number of previous observations to predict future observations.

High Frequency Financial Data Analysis

Technologies & facilities: Resources of interest to other academics or enterprise collaborators

As well as possessing a vital nexus of expertise on Time Series Analysis (amongst a range of other Simulation/Modelling/Complex Systems specialisms, the ARC-SYM Centre has two condominium shares (each 96 cores) at Irish Centre for High End Computing (ICHEC). It also possesses many diverse platforms for data visualization & simulation.

How and why to collaborate with us

The Time Series Analysis group provides a unique nexus of capabilities in Ireland in the area. It is actively engaged in a range of projects with Industrial as well as DCU Internal and External Research partners. The group would have a wide portfolio of solutions covering a broad range of conditions but bespoke solutions can be developed as required. Prospective collaborators are encouraged to arrange a meeting early in the life cycle of a potential collaboration to permit a range of solutions and funding sources to be examined.

Pedestrian Behaviour Modelling in Large Urban Networks: Extracting flow data from pedestrian movement

Opportunities for enterprises: Engagement opportunities

We have engaged with industrial partners in many of our research projects to date. Current partners include:

  • SIGMAR Recruitment

Past engagements have involved provision of simulation and modelling for the following:

  1. Sigmoid Pharma (design of optimum drug delivery systems)
  2. Airtricity (Wind-turbine design)

Stochastic Methods for Modelling Drug Delivery Systems (DDS): Visualisation of the Cellular Automata simulation for DDS

Opportunities for enterprises: Consultancy services

We would see the following as likely industry growth areas over the short- to medium-term:

  • Modelling Changes in customer behaviour (especially customer churn across different timescales)
  • Agricultural data analysis for optimization of yields
  • Logistics, Supply Chain and Process Modelling for SMEs to optimise cash flow and resource usage

Opportunities for enterprises: Case studies

The following are case studies of engagement with industry in the past:

  • Betting Data analysis with a leading bookmaker
  • Energy time series analysis with major multinational electric car manufacturer
  • Wind energy modelling with a large Irish public utility company
  • Drug dissolution modelling using mathematical/probabilistic methods

Data Analysis of Lifelogging                                                          Biological/Biometric Time Series

 

Genetic Regulatory Network Modelling                                         Immune Response Modelling

 

Publications/Conference papers/Reviews/Books/Software/Outputs etc

  1. Na Li, Martin Crane, Cathal Gurrin, Heather J Ruskin (2016) Finding Motifs in Large Personal Lifelogs, Proceedings of the 7th Augmented Human International Conference 2016, Pages 9, ACM
  2. Marija Bezbradica, Martin Crane, Heather J Ruskin (2016) Applications of High Performance Algorithms to Large Scale Cellular Automata Frameworks Used in Pharmaceutical Modelling, Journal of Cellular Automata, 11(1)
  3. 3.       Adel M. Alsharkasi, Martin Crane and Heather J. Ruskin (2016) Evaluating the Volatility Behaviour in Irish ISEQ

Overall Index Using GARCH Models, British Journal of Economics, Management & Trade, 13(1): 1-13

  1. Alina Sîrbu, Martin Crane, Heather J Ruskin (2015) Data integration for microarrays: enhanced inference for gene regulatory networks, Microarrays, Volume 4(2), Pages 255-269
  2. Marija Bezbradica, Heather J Ruskin, Martin Crane (2015) Comparative analysis of asynchronous cellular automata in stochastic pharmaceutical modelling, Journal of Computational Science, Volume 5(5), Pages 834-840

Epigenetic Modelling: Comparative Correlation Structure of Colon Cancer Locus Specific Methylation:

Characterisation of Patient Profiles and Potential Markers across 3 Array-Based Datasets: D1,D2,D3  

 Neuropsychiatric Genomics

Research theme: Neuropsychiatric Genomics

 

The focus of this area of research is on the genetic epidemiology of complex neurological diseases, and using computational and functional genomics approaches to deciphering pathogenic molecular mechanisms. We have been involved in several large genome-wide association studies, which have been successful in identifying genetic risk variants associated with complex phenotypes such as Alzheimer’s disease and schizophrenia. However, there is a substantial gap between our ability to identify these loci and our understanding of how the identified risk variants contribute to the underlying disease pathogenesis. By leveraging large-scale functional and comparative genomic datasets, we aim to functionally annotate GWAS loci, in order to provide insights into potential molecular mechanisms that can be tested/validated through disease-relevant, high-throughput functional assays.

 

Pathways implicated in Alzheimer’s disease pathogenesis through analysis of large-scale genomewide association studies. Strong relationships are revealed between negative regulation of endocytosis and cholesterol transport, and many of the pathways are related to the immune response (work with Cardiff University) (Denise Harold, Biotechnology)

 

What’s the big idea?

 

Identifying causal relationships between genetic variants and disease risk will help to elucidate pathogenic processes at the molecular level and to identify tractable targets for therapeutic intervention. As discovery of risk variants grows, identifying the causal variants and their mechanisms will ultimately aid in improving predictions of disease onset, and in determining sub-types of disease, which will be particularly important for developing a precision medicine approach to treatment.

 

How and why to collaborate with us

 

Our focus is on neuropsychiatric genomics, particularly Alzheimer’s disease, and would be complementary in nature to those working in either clinical or cell biology research in this field. The pipelines generated through my research are also applicable to other complex diseases and we would be happy to collaborate with researchers working on both neurological and non-neurological phenotypes.

 

 

Identification of a pathogenic deletion in the BRCA2 gene resulting in a frameshift. The mutation was identified using a next generation sequencing gene panel (work with Elda Biotech).

 

 

 

International engagements

 

MRC Centre for Neuropsychiatric Genetics & Genomics (Cardiff), International Genomics of Alzheimer’s Project (IGAP) Consortium, PERADES Consortium

 

Manhattan plot of a genomewide association study of Alzheimer’s disease (AD). In addition to the known involvement of the APOE gene in AD, two novel susceptibility genes were identified: CLU and PICALM  (work with Cardiff University).

 

Selected Publications:

  • Shared genetic contribution to Ischaemic Stroke and Alzheimer's Disease. Traylor M, Adib-Samii P, Harold D; Alzheimer's Disease Neuroimaging Initiative; International Stroke Genetics Consortium (ISGC), UK Young Lacunar Stroke DNA resource, Dichgans M, Williams J, Lewis CM, Markus HS; METASTROKE; International Genomics of Alzheimer's Project (IGAP), investigators. Ann Neurol, 2016.
  • Identification of Genetic Factors that Modify Clinical Onset of Huntington's Disease. Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium. Cell, 2015, 162(3):516-26.
  • Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Lambert JC, Ibrahim-Verbaas CA, Harold D*, et al. Nat Genet, 2013, 45 (12) 1452-8. * Joint first author
  • Common variants at ABCA7 MS4A6A/MS4A4E EPHA1 CD33 and CD2AP are associated with Alzheimer's disease. Hollingworth P, Harold D*, et al. Nat Genet, 2011, 43 (5) 429-35. * Joint first author
  • Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Harold D, Abraham R, Hollingworth P, et al. Nat Genet, 2009, 41 (10) 1088-93.

 

Selected Invited Presentations:

2015       Speaker at Molecular Medicine Ireland Techniques and Strategies Course, Dublin, Ireland.

2015       Speaker at 5th Irish Next-Generation Sequencing Conference, Dublin, Ireland.

2013       Speaker at NHS Clinical Genetics & Genetic Counselling conference, Cardiff, UK.

2012       Speaker at the European Human Genetics Conference (ESHG), Nuremberg, Germany.

2010       Speaker at the Alzheimer's Association International Conference, Honolulu, USA.

 

Funding

 

•EU Joint Programme – Neurodegenerative Disease Research (JPND) - Defining Genetic, Polygenic and Environmental Risk for Alzheimer’s Disease using multiple powerful cohorts, focussed Epigenetics and Stem cell metabolomics. UK award: Prof J Williams, Dr D Harold, Dr V Moskvina, Prof J Hardy, Dr R Guerreiro. 1/5/14 - 30/4/17, £994,348. Total award = €3,171,567

•Medical Research Council (Programme Grant) - Further defining the genetic architecture of Alzheimer's disease.  Prof J Williams, Prof P Holmans, Prof H Morris, Prof M Owen, Prof M O’Donovan, Prof M Li, Dr V Moskvina, Dr D Harold. 28/8/13 - 27/8/18, £2,739,220

•Enterprise Ireland Innovation Voucher – Elda Biotech, Dr D Harold, 03/11/14 – 15/02/15, €6,150

•Alzheimer’s Research UK (Network Co-operation grant) - Identifying factors influencing the earliest changes in Alzheimer's disease development. Dr P Edison, Dr D Harold, Prof DJ Brooks. 01/11/12 - 31/10/13, £66,603

•European Union FP6 - Dyslexia Genes and Neurobiological Pathways (NeuroDys).  Prof J Williams, Prof M O’Donovan, Prof M Owen, Prof P Holmans, Prof N Lench, Dr G Hill, Dr D Harold, Dr V Moskvina. 01/07/06 - 30/06/09, £340,025

•Wellcome Trust Value in People Award. Dr D Harold. 01/02/2006 - 31/10/2006, £15374 

 Heat and Fluid Flow Research

 


Research Theme: Heat and Fluid Flow Research

 

The Heat and Fluid Flow Group aims to support research and development in fluid flow with a particular focus on engineering processes found in energy and water based environmental systems. It has a strong track record of targeted applied and basic research having received support from Enterprise Ireland, Science Foundation Ireland and the EU for several academic and industrial collaborations.  Its core expertise is in Computational Fluid Dynamics where it has developed specialised methods and codes to examine unconventional flow problems but also has extensive experience of commercial CFD and pre/post-processing tools. In recent years, it has also established substantial experimental capabilities for non-invasive visualisation and characterisation of certain specialised fluid dynamics problems including fluid-structure interaction and multiphase fluid flow.

 

 

We foster research on Computational Fluid Dynamics (CFD) modelling of complex heat and fluid flows found in energy systems including heat exchangers and heat engines and in a range of treatment processes such as waste water filtration (Yan Delauré, Mechanical Engineering).

 

What’s the big idea?

 

Although commercial CFD tools have evolved to allow accurate simulation of increasingly complex Fluid and thermal systems, more challenging flow processes involving multiple interactions between multiple fluid and solid phases and deformable and/or moving immersed solids continue to require advanced skills either to develop tailor made solutions or to customise and validate existing solutions.

 

Resources of interest to other academics or enterprise collaborators

 

Novel computational solvers based on the OpenFOAMTM libraries for the study of:

  • air-water flow
  • rotating machinery
  • immersed and highly flexible structures

 

Experimental characterisation tools:

  • Planar Particle Image Velocimetry
  • Digital Image Correlation for structural deformation analysis
  • Shadow Sizing for particulate flow characterisation

 

 

CFD Modelling of rag handling by sewage water

pumps: flow through a single impeller pump

 

How and why to collaborate with us

 

The group offers unique capabilities in Ireland for the study of fluid structure interaction in multiphase fluid flow. It is actively engaged in method and code development through three ongoing industrial projects and continues to look for new challenges. Existing computational solutions cover a broad range of conditions but may be further developed to account for more specific needs. Its experimental capabilities are primarily used to provide experimental verification but can also be adapted to study specific flow conditions and address specific needs. 

 

 

CFD Modelling of Wave Interaction with Ocean Wave Energy Converters: Regular Wave interaction with constrained floating cylinder

 

Opportunities for enterprises: Engagement opportunities

 

Engagement with industrial partners has been a key feature of most research projects to date. Current partners include:

  • Ireland
    • Sulzer Pump Solution Ireland Ltd.
    • Exergyn Ltd
    • ABP Food Group

 

  • International
    • EU Partners under H2020 Innovation Action Project

 

 

 

Enhanced Heat Transfer by Bubble Injection: Bubble interaction with free convection thermal boundary layer

 

Opportunities for enterprises: Case studies

 

Project title: Development of computational models for cloth fluid interaction and pump simulation (2 Projects)

Funding: Enterprise Ireland Innovation Partnership (2015-2017) and Irish Research Council Employment Based Research Scholarship (2014-2018)

Researchers: Dr Yan Delauré (PI), Abdulaleem Albadawi (Post-Doctoral Researcher) and Mathieu Specklin (PhD)

Collaboration: Sulzer Pump Solutions Ireland

 

Description: 

The core business of the project partner, Sulzer Pump Solutions Ireland Ltd, is the provision of pumping technology for the waste water sector and other process applications. The company has built a strong reputation from their pump’s robust rag handling capabilities and continues to invest in research and development. It has been collaborating with ARC-Sym’s Heat and Fluid Flow Group since 2012 to develop innovative computational solutions better suited to its very specific needs. The code development is being supported by experimental characterisation of fluid structure interaction problems both at DCU and at the company’s product development centre.

 

 

Pump simulation using scale resolving turbulence model (left) Fluid Structure visualisation (right)

 

Project title: Feasibility Assessment of Computational Fluid Dynamics Modelling of Heat Engine

Funding: Enterprise Ireland Fast Track Co-Fund Innovation Voucher

Researchers: Dr Yan Delauré (PI)

Collaboration: Exergyn Ltd

 

Description: 

Exergyn’s heat engine converts low grade thermal energy into usable mechanical power. Ensuring an optimal distribution of heat within its core is critical to achieving high energy conversion but presents a number of significant challenges. The company contacted DCU’s Heat and Fluid Flow group to assess the suitability of Computational Fluid Modelling as a practical design tool. This gave the company access to high performance computational resource which has proven essential given the system’s complexity and size. Initial work has been supported by an Enterprise Innovation Voucher and has led to the preparation of further research funding applications to support more in-depth research.

 

Refer to company’s website: www.exergyn.com 

  Infection Genomics

 


Research Theme: Infection Genomics

 

Our research focuses on using genomics, population genetics and evolutionary modelling of DNA sequences to infer the origin, spread and transmission of infectious diseases. This has two main paths: the experimental evolution of drug resistance in pathogens, and the population genomics of pathogen samples from infected patients. We have discovered treatment tolerance mutations at multiple levels associated with penicillin-based, heavy metal and lipid-based drugs during work on single-cell Leishmania parasites and in bacteria Staphylococcus aureus. We are also investigating the alarming spread of E. coli ST131 in collaboration with other groups. Although E. coli is a standard experimental model for studying evolution in the lab, little investigation of natural variability has been completed. Tracking the transmission of toxin- and virulence-related genes in hospital and community settings provides information on the (in)adequacy of current (non-genomic) bacterial profiling diagnostics, so that the sources of novel ST131 types can be identified. We dissect such epidemiological patterns using bioinformatic and statistical methods to infer likely characteristics of new samples. We have also worked on analysing breast cancer genomic/transcriptomic data from patients, which overlaps with work on infectious disease in terms of detecting signatures of mutation patterns. We also assist others in analysing high-throughput molecular data from Arabidopsis, Leishmania, micobioata, influenza viruses and other species to facilitate analyses of diagnostics, evolution and genetic diversity.

 

Analysis of Leishmania parasite genomes in the Indian subcontinent (ISC) reveals the mixing of populations (green, black, brown, blue) to generate drug-resistant hybrids now spreading from India into Nepal (work conducted with the Sanger Institute UK & ITM Antwerp Belgium).

 

 

Group members                    Position                  Orcid

Tim Downing                         Group leader        0000-0002-8385-6730

Simone Coughlan                 PhD student          0000-0002-0181-2399

Arun Decano                        PhD student          0000-0002-6058-6483

 

Current projects:

(1) Escherichia coli ST131 genomes from long-term care facilities highlight subtype displace-ment and pervasive recombination (with Martin Cormican, Dearbhàile Morris and others, NUI Galway).

(2) Genomic and transcriptomic variation associated with the in vitro induction of resistance to oxacillin in Staphylococcus aureus (with James O’Gara and others, NUI Galway).

(3) Genome assembly and comparison of Leishmania alderi, guyanensis and naiffi genomes from zoonotic sources (with Wellcome Trust Sanger Institute and Charite University).

(4) Genomic and metabolomic profiles of experimentally induced paromomycin resistance in Leishmania parasites (with Wellcome Trust Sanger Institute, Institute of Tropical Medicine Antwerp and Strathclyde University).

(5) Imputation of recombination on drug-resistant Leishmania genomes (with Wellcome Trust Sanger Institute and Institute of Tropical Medicine Antwerp).

 

See popular press article in Irish Examiner

www.irishexaminer.com/ireland/major-black-fever-breakthrough-by-irish-scientists-388916.html

 

See popular press article in Irish Medical Times

www.imt.ie/newsletter/2016/03/galway-team-finds-link-to-parasitic-drug-resistance.html

 

 

The genealogy of 84 drug-resistant Escherichia coli ST131 bacterial genomes isolated in Ireland. The genetic populations are shown as red (A), blue (B), green (C) and pink (AC). This shows the transmission patterns between infected people (work conducted with NUI Galway) (Arun Decano & Tim Downing, Biotechnology)

 

What’s the big idea?

 

Our work aims to improve public health because bacterial infection and drug resistance are abundant worldwide and nationally. Drug resistance estimates based on DNA has predictive power akin to standard methods that are more labour-intensive. So our work will facilitate better diagnostics and using high-throughput molecular pathogen screening as a standard medical tool.

 

Resources of interest to other academics or enterprise collaborators

 

The Infection Genomics laboratory is equipped with a Dell PowerEdge R430 computer server with two Intel 2.4 GHz processors with a maximum total RAM of 288 Gb providing 24 cores for complex multi-threaded bioinformatic research.

 

How and why to collaborate with us

 

We collaborate with researchers in the medical and life sciences. Prospective collaborators should ideal arrange a meeting early in the life cycle of a potential collaboration to obtain input on population genomic or bioinformatic considerations for experimental design and downstream analysis.

 

 

Multiple genetic routes to drug resistance via mutations of the LdMT gene for dosage for a "Sb-S" Leishmania parasite during dosing with miltefosine from 0 to 74 μM (x-axis). The wild-type (black, A691) changes copy number, and then either gets deleted (ΔLdMT, biege) or is mutated (P691, purple) (work with the Sanger Institute UK & Strathclyde University).

 

Opportunities for enterprises: Consultancy services

 

  • Analysis of high-throughput molecular data
  • Computational diagnostics development
  • Experimental design of genome-based work

 

 

 

International engagements

 

Wellcome Trust Sanger Institute,  Charite University, Institute of Tropical Medicine Antwerp, Strathclyde University and Centre Hospitalier Universitaire de Nice.

 

Publications/Conference papers/Reviews/Books/Software/Outputs etc

 

Recent Publications

 

  • Imamura H*, Downing T*, Van de Broeck F*, Sanders MJ, Rijal S, Sundar S, Mannaert A, Vanaerschot M, Berg M, De Muylder G, Dumetz F, Cuypers B, Maes I, Decuypere S, Rai K, Uranw S, Bhattarai NR, Khanal B, Prajapati VK, Stark O, Schoenian G, De Koning H, Settimo L, Vanhollebeke B, Roy S, Ostyn B, Boelaert M, Maes L, Berriman M, Dujardin JC, Cotton JA. Evolutionary genomics of epidemic visceral leishmaniasis in the Indian subcontinent. Elife 5:e12613 (2016) DOI: http://dx.doi.org/10.7554/eLife.12613.001
  • Shaw CD*, Longchamp J*, Downing T*, Imamura H*, Freeman TM, Cotton JA, Sanders M, Blackburn G, Dujardin JC, Riyal S, Khanal B, Illingworth CJR, Coombs GH, Carter KC. In vitro selection of miltefosine resistance in promastigotes of Leishmania donovani from Nepal: genomic and metabolomic characterisation. Molecular Microbiology (2016) 99(6):1134-48. doi: 10.1111/mmi.13291
  • Kitavi M, Downing T, Lorenzen J, Karamura D, Onyango M, Nyine M, Ferguson M, Spillane C. 2015. The triploid East African Highland Banana (EAHB) genepool is genetically uniform arising from a single ancestral clone that underwent population expansion by vegetative propagation. Theoretical and Applied Genetics (2016) DOI 10.1007/s00122-015-2647-1
  • Kelly H, Downing T, Smith TJ, Tuite N, Kerin MJ, Dwyer RM, Clancy E, Barry T, Reddington K. Cross platform standardisation and normalisation experimental pipeline for use in the biodiscovery of dysregulated human circulating miRNAs. PLoS One (2015) 10(9):e0137389.
  • Downing T. Tackling drug resistant infection outbreaks of global pandemic Escherichia coli ST131 using evolutionary and epidemiological genomics. Microorganisms (2015) 3(2):236-267. Part of “Antibiotic Resistance Mechanisms” special issue.
  • Coughlan S, Barreira S, Seoighe C, Downing T. Genome-wide variant discovery using sequence assembly, mapping and population-wide analysis. pp. 51-80. Book chapter in “Bioinformatics and data analysis in microbiology” (2014). Caister Academic Press.

Recent Posters

  • Coughlan S, Schonian G, Berriman M, Downing T. Genome assembly and characterisation of a new species of Leishmania Computational Biology and Innovation Symposium 2015, UCD, Dublin, Ireland (2015).
  • Coughlan S, Rudkin JK, O'Gara JP, Downing T. Multiple genomic and transcriptomic switches drive oxacillin resistance in community-acquired MRSA. ISMB/ECCB Conference, Dublin, Ireland (2015).
  • Downing T, Ludden C, Cormican M, Morris D. Haplotype-based inference of recombination in Escherichia coli ST131 genomes highlight subtype displacement in long-term care facilities. Intelligent Systems for Molecular Biology, Dublin (2015) F1000Research 4(ISCB Comm J):316 (doi: 10.7490/f1000research.1110065.1).
  • Downing T, et al. Genomic ancestry blocks decipher population admixture and epidemiology in a monomorphic parasite. Human Genome Variation and Complex Genome Analysis, Belfast, UK (2014).
  • Coughlan S, Schonian G, Berriman M, Seoighe C, Downing T. Harnessing related species and samples data to create and optimise draft genome sequences for Leishmania species. Virtual Institute of Bioinformatics and Evolution (VIBE), IT Carlow, Ireland (2014).
  • Coughlan S, Seoighe C, Schonian G, Berriman M, Downing T.  Harnessing related species and samples data to create and optimise a draft genome sequence for Leishmania species. ISMB/ECCB Conference, Berlin, Germany (2014).
  • Coughlan S, Seoighe C, Schonian G, Berriman M, Downing T. Harnessing related species and samples data to create and optimise a draft genome sequence for Leishmania species. Virtual Institute of Bioinformatics and Evolution (VIBE), NUI Galway, Galway, Ireland (2013).

Recent Talks

  • Coughlan S, Rudkin JK, Black N, Gallagher L, O’Gara JP, Downing T. The genetics of restricted virulence in community-acquired MRSA. Virtual Institute of Bioinformatics and Evolution symposium, DCU, Dublin, Ireland (2015).
  • Decano A, Lee JH, Pascua P, Choi YK. Zoonotic potential of a novel reassortant H1N2 swine influenza virus with a gene constellation derived from multiple viral sources. UCD Computational Biology PhD Symposium. University College Dublin, Ireland (2015).
  • Downing T, Ludden C, Cormican M, Morris D. Genomic tracing of subtype displacement and mixing in pandemic Escherichia coli. Invited seminar. Department of Biology, Maynooth University, Ireland (2015).
  • Coughlan S, O'Gara JP, Rudkin JK, Downing T. Multiple genomic and transcriptomic switches drive oxacillin resistance in community-acquired MRSA. Computational Biology and Innovation Symposium, UCD, Dublin, Ireland (2014).
  • Coughlan S, Seoighe C, Schonian G, Berriman M, Downing T. Harnessing related species and samples data to create and optimise draft genome sequences for Leishmania species. British Society for Parasitology Spring Meeting, Cambridge, UK (2014).
  • Downing T, et al. Extensive and adaptive genome structure variation drives the evolution and epidemiology of visceral leishmaniasis in the Indian subcontinent. Evolution of Drug Resistance workshop, Kavli Institute for Theoretical Physics, University of California Santa Barbara, USA (2014).
  • Downing T, Ludden C, Cormican M, Morris D. Escherichia coli ST131 genomes from long-term care facilities highlight subtype displacement and pervasive recombination. Evolution of Drug Resistance workshop, Kavli Institute for Theoretical Physics, University of California Santa Barbara, USA (2014).
  • Downing T, et al. High-throughput genome sequencing deciphers population admixture and epidemiology in a monomorphic parasite. Next Generation Sequencing meeting, Trinity College Dublin, Ireland (2014).
  • Coughlan S, Seoighe C, Schonian G, Berriman M, Downing T. Harnessing related species and samples data to create and optimise draft genome sequences for Leishmania species. Computational Biology and Innovation Symposium, UCD, Dublin, Ireland (2013).

Other reports

  • “Wikis help independent learning and transparent assessment in large classes” (DCU Faculty of Science Blog https://facultydiary.wordpress.com/2016/03/31/).

Awards

 

  • DCU O’Hare Ph.D. fellowship grant (2015-2019) “A population phylogenomic analysis of the origin and spread of pandemic Escherichia coli ST131”.
  • DCU Enhancing Performance 2015 (2015-2016) “Computer resources for genomics and computational biology research”.
  • NUI Galway Ph.D. Fellowship grant (2012-2016) “Pathogen genomics and evolution”.
  • Naughton Notre Dame Undergraduate Research Fellowship grant (2016) “Biomarker discovery in hybrid parasite genomes”.