Short Courses
In addition to the student talks and plenary sessions, we are offering a series
of short courses in conjunction with the conference. These courses will be offered
during the afternoon of Friday, April 21, 2017 at 1:00pm. The short courses are
open to all registrants, and there is no need to pre-register for any particular
coruse. Upon arrival at the conference, you may choose in which course, if any, you
would like to participate.
Mathematical models of oscillation and synchronization on networks
Dr. Mark Panaggio, Hillsdale College
Oscillation is a fundamental feature of many biological systems. At
the cellular level, oscillation is observed in spiking neurons and
the contraction and relaxation of muscle tissue. Oscillation also
occurs on a larger scale in the dynamics of swarms and circadian
rhythms. In this short course, we will explore various mathematical
models of “coupled oscillators” and investigate the internal
dynamics of individuals as well as the collective behaviors of
networks of oscillators. Along the way we will discuss theoretical
results, applications and open questions pertaining to the emergence
of synchronization in nature.
Please bring a laptop to this session!
Modeling RNA secondary structures using graphs
Dr. Manda Riehl, University of Wisconsin, Eau Claire
RNA is single stranded and can form complicated base-pairings, e.g. stem-loops, cloverleafs, and pseudoknots. For many RNA molecules, the structure made by these pairings (called its secondary structure) can be as important to the function of the molecule as the sequence itself. We will investigate several graph theoretic models for RNA secondary structure, particularly matchings and trees, and the assumptions made in each model. We will also look at some of the information available on these RNA secondary structures in online databases.
Introduction to Data Science
Dr. Mark Daniel Ward, Purdue University
We will have a hands-on overview of some of the tools that data scientists use for
working with data, including large data sets. The workshop topics can be slightly
flexible and open to discussion, depending on the interests of the participants.
At a minimum, we will introduce students to R and RStudio, data visualization, and
perhaps some tools for scraping and parsing XML directly from the web and processing
the scraped data in R. All participants are encouraged to bring a laptop...and to be
excited to learn about some of the introductory nuts and bolts of data science.
No computational background is needed for this workshop.
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