Application Deadline: August 10, 2018
Individuals will be notified of acceptance to the workshop by August 31st, 2018
Goals of this workshop include:
- Identify the questions, challenges, tools, and needs for microbiome studies at Ohio State University (OSU) and in the greater Columbus area.
- Stimulate interdisciplinary collaborations at OSU and in the greater Columbus area (e.g. Nationwide Children’s Hospital, Battelle).
The intended workshop participants are faculty / PIs who are laboratory scientists, mathematicians, statisticians, or metabolic modelers working on or interested in questions that involve the microbiome.
As such, preference will be given to OSU or local faculty applicants for this workshop.
From the bacteria in our guts, to microbes involved in biodegradation and crop growth, to viruses in the ocean, some of Earth’s tiniest organisms play some of the most important roles in global health, food production, and climate change. Advances in metagenomic sequencing technology including 16S, viromics, and mycobiomics - along with metabolomics, transcriptomics, and proteomics allow us to characterize these complex microbial communities and begin to understand their functions. This Big Data creates opportunities for data driven discovery and new data analytics, but Big Data also comes with challenges: Meaningful integration of multi-omic data has become increasingly critical to microbiome studies as recent work highlights the importance of community dynamics, interactions, and microbial ecology over the roles of individual microbes. For example, microbial metabolisms are now recognized to often be ‘distributed’ across consortia; viruses manipulate microbial metabolisms and population dynamics, and co-occurring fungi in most ecosystems are virtually unstudied but likely play key roles as well. Data integration techniques range from correlations to network analyses to genome-scale microbial community metabolic models that assess metabolite flux to ecosystem models that provide predictive power of which organisms drive key features of the system. Some of these techniques, like correlations, accommodate many types of –omic data but cannot account for the complex biology or ecology of a system. Other techniques, like metabolic modeling, better account for this complexity, but do not yet integrate phenotypic –omic data (i.e. metabolomics, proteomics) well. Each of these techniques has advantages and limitations and new computational tools for data integration and modeling have rapidly developed over the last 2 years. Besides data integration, Whether studying environmental, gut, or industrial microbes, the ability to accurately identify and predict the structure and function of microbial communities has far-reaching potential and paves the way for microbial engineering in bioremediation, probiotic development, and sustainable agriculture.
In this 3 day workshop, we will take a genome to phonome approach with broad perspectives provided by mathematicians, biologists, and statisticians. We will also develop interdisciplinary working subgroups to consider the questions, challenges, tools, and needs of data integration and modeling in microbiome studies. Each participant will present a short talk (5 minutes, 3 slides) highlighting his or her research, perspectives, and challenges. The goal is to help develop a broadly collaborative community of math-enabled microbiome scientists with common research goals.
This workshop is co-sponsored by the Mathematical Biosciences Institute and the Infectious Diseases Institute at Ohio State University.
|Wednesday, October 10, 2018|
|Thursday, October 11, 2018|
|Friday, October 12, 2018|
|Dawes, Adrianaemail@example.com||Department of Mathematics / Department of Molecular Genetics, The Ohio State University|
|Hale, Vanessafirstname.lastname@example.org||Department of Veterinary Preventive Medicine, The Ohio State University|
|Papin, Jasonemail@example.com||Department of Biomedical Engineering, University of Virginia|
|Sullivan, Matthewfirstname.lastname@example.org||Department of Microbiology, The Ohio State University|