Richard Barker, Bil Alverson, Ricardo Kriebel ,
Date and Time: Oct 29, 2014 (12:30 PM)
Location: Orchard room (3280) at the Wisconsin Institute for Discovery Building
In many scientific disciplines, new technologies are enabling researchers to obtain measurements of unprecedented scale and resolution. These huge data sets present many new challenges and opportunities for the experimental scientists generating the data and for researchers like those in the SILO community developing data analyses. In this talk, three field and bench scientists from Botany will outline big-data projects they are working on and discuss some of the challenges they are facing.
1) Plants growing in microgravity must respond to stresses unlike those they have encountered in their evolutionary histories. Richard Barker will discuss several experiments in which a number of different Arabidopsis thaliana ecotypes and mutants have been grown in space, including some experiments currently orbiting on the International Space Shuttle. In these experiments, genome-wide RNA Seq data from tens of samples must be analyzed. What is needed are new tools or methods that quickly compare the results to reveal interesting candidate genes and intuitively visualize other subtle trends within the context of the broader data sets that involve approximately 40,000 genes.
2) The Dimensions of Biodiversity Project comprises several disparate types of data on the ecology and genetics of Wisconsin's plant species, including field observations, molecular (i.e. DNA sequence) and climatological data. These data promise to provide a valuable resource for researchers trying to model changes in biodiversity in light of climate change, as well as for a variety of other critical areas of research. Bil Alverson will describe these data, discuss their local management and archival targets, and give examples of the research questions they will address.
3) The morphology of plants, including shapes of their flowers, pollen, and other structures are key phenotypes for classification and often have functional significance. However, most analyses that incorporate morphological features discretize these measurements, sacrificing much of the power of the observations. Ricardo Kriebel will discuss his attempts to develop tools to extract richer morphological statistics from a multitude of images and to understand the evolution of these complex traits by mapping their statistics onto phylogenetic trees inferred from DNA sequence data.
After short presentations, we will brainstorm about building mutually beneficial connections between the SILO community and data-gathering scientists, not only with these three scientists but also with the hundreds of others on campus in similar situations.