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NIMBioS Tutorial

Computing in the Cloud

Tutorial group photo.

Topic: Computing in the Cloud: What Every Computational Life Scientist Should Know

Meeting dates: April 6-8, 2014

Location: NIMBioS at the University of Tennessee, Knoxville

Russell Zaretzki, Statistics, Univ. of Tennessee
Michael Gilchrist, Ecology & Evolutionary Biology, Univ. of Tennessee
Eric Carr, NIMBioS, Univ. of Tennessee
George Ostrouchov, Oak Ridge National Laboratory, National Institute for Computational Sciences, and Univ. of Tennessee
Brian O'Meara, Ecology & Evolutionary Biology, Univ. of Tennessee

This tutorial brought together a diverse set of computational biologists and modelers who wanted to expand their expertise and learn how to harness big data and computation using the R language. 

A wide range of HPC/Cluster/Cloud computing resources exist and are accessible to researchers, such as Amazon EC2, NSF XSEDE, local clusters, and simple multiprocessor shared memory machines.  Participants learned about the strengths and weaknesses of the various platforms and how to enable R to utilize them.  The strengths and limitations of R for big data and big computation were also discussed. Moving beyond these basics, further sessions provided participants with hands on experience in the following areas:

  1. Learn about the packages, tools, and data structures that are available in R for computing on HPC resources
  2. Understand tools such as Rcpp that allow R to easily interface with compiled code for improved performance
  3. Handle big matrix computations with the pbdR packages
  4. Produce elegant, publication quality graphics with the ggplot2 package

In addition to the fundamentals, the tutorial gave attendees a perspective on how these tools can be put to use in biological research.  Tutorial examples included applications such as Bayesian mixed models in genomics, phylogenetic biogeography, approximate Bayesian computation, and multivariate data reduction in ecological models.  Finally, a special session on teaching with R provided insights on how to bring computational science research into the undergraduate classroom.

This hands-on tutorial gave participants an opportunity to begin applying these tools to their own problems.  Presentations and sample codes were available for all tutorial sessions.  Attendees also consulted with presenters and platform experts to identify the right tools for their problems.  

Participants should have a solid working knowledge of the R language.  Experience with a lower level programming language (C, C++, Fortran) will also be beneficial but is not required.

Descriptive Flyer

Computing in the Cloud WordPress Site.

Presentations were available for viewing via live streaming during the workshop.

Playlist of online videos.

photo. Summary Report. TBA


Software, Data & Websites

Schmidt D, Chen WC, Ostrouchov G, Patel P. 2013. pbdBASE: An R package update. [Online]

Schmidt D, Chen WC, Ostrouchov G, Patel P, R Core Team. 2013. pbdDMAT: An R package update. [Online]

Evaluation report (PDF)

A goal of NIMBioS is to enhance the cadre of researchers capable of interdisciplinary efforts across mathematics and biology. As part of this goal, NIMBioS is committed to promoting diversity in all its activities. Diversity is considered in all its aspects, social and scientific, including gender, ethnicity, scientific field, career stage, geography and type of home institution. Questions regarding diversity issues should be directed to You can read more about our Diversity Plan on our NIMBioS Policies web page. The NIMBioS building is fully handicapped accessible.

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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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