Computing, genomics and analytics workshop


Register for the Launch at this link

Register for the Workshop at this link

ARC-SYM members address complex and dynamic problems in science, engineering, health and maths by developing appropriate models and testing ideas. Investigation of systems at all scales relies on knowledge of their design and operation, the relevant data, and translating this into useful information. We use our interdisciplinary expertise with DCU and national high-performance computing infrastructure to work with different academic and commercial groups to provide flexible and specific solutions in the area of research computing. This is fundamental to creating simulations and predictive analytics designed to verify, inform and develop information on complex systems.

Workshop timetable

The ARC-SYM Launch Event is at 1000-1230 in the Invent Seminar Room

The Workshop Venue is Q205, 2nd floor of DCU Business School

Morning 0930-1300
Afternoon 1400-1730
Launch Event (Invent Seminar Room)
Genome-wide Association Analysis (2-5)
Accessing Gene/Protein Databases (930-1)
Introduction to R (2-5)
Getting your data into R (930-1)
How to analyse microarray data with R (2-5)
Applications of Time Series Analysis (930-1)
Basic & Bayesian Statistics, Classifiers, Pattern recognition (2-5)
Programming Big Data with R (10-1)

Investigation of any system, at whatever scale, relies on knowledge of its design and operation, the relevant data and translating this into useful information. This is seldom straightforward in practice. Given recent advances in computing power and the accompanying hype, it is easy to view data issues as overcome, or to focus only on this aspect of problem-solving. Unfortunately, not all quantities can be measured directly, and abundance is often deceptive or can obscure key findings. If system components are outside our physical control, - too large, too small or otherwise constrained by ethics, cost, or tractability, then typically some type of model is needed. Evaluating its description and performance and choosing the appropriate statistical or computational methods to use is vital. This improves our knowledge of the systems’ attributes and enables better testing, graphical visualisation and communication with other scientists.

So is your system complex due to
  • its description? many components and how these relate? the model, the maths, the
  • parameterisation?
  • inaccessibility of scale, whether micro or macro? What to measure?
  • patient diversity, the spectrum of disease experience or the underlying mechanisms involved?
  • confidentiality, intricacy of operation, strategy and finance?
  • the data – spectrum and quality, too much? too little? How to filter or integrate several types?
  • legacy and when to discard?
  • the appropriate computational tools and statistical techniques? What and when to use?

If any of these questions sounds familiar, come to sessions of the ARC-SYM Workshop week, September 5th-9th

Why bother with a workshop?
Skills learned are used at least monthly by most participants, irrespective of academic discipline or level. Participants generally use the new skills and knowledge to do better research (50%), communicate better with bioinformaticians and statisticians (48%), verify ongoing experiments (34%), and improve publication quality (28%) (PLoS Computational Biology).

Participant requirements:
1. Laptop with admin permissions and (optionally) own dataset
2. R and R Studio fully installed, working and tested in advance
3. Prior experience with R for sessions on Wednesday (“Getting your data into R”, “How to analyse microarray data with R”) and Friday ("Programming Big Data with R"). Basic knowledge of statistics for Thursday session ("Statistics, classifiers and clustering").
4. Consider for each session: (i) why do you want to attend? And (ii) why is it relevant to your area of interest?

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