Emerging Statistical Challenges & Methods for Analysis of Human Microbiome Data (19w5221)
Organizers
Yijuan Hu (Emory University)
Hong Gu (Dalhousie University)
Shyamal Peddada (University of Pittsburgh)
Michael Wu (Fred Hutchinson Cancer Center)
Description
The Banff International Research Station will host the "Emerging Statistical Challenges and Methods for Analysis of Human Microbiome Data (HALF)" workshop in Banff from September 15 to September 20, 2019.
Studies on the human microbiome have revealed that differences in microbial communities is associated with many human disorders, such as Crohn’s disease, type II diabetes, asthma, obesity, and even autism, Alzheimer’s disease and some cancers. The microbiome is an attractive target for establishing new biomarkers for diagnosis, disease progression and prognosis, and for developing low-cost, low-risk, interventions. Given the potential effect of microorganisms on public health and precision medicine, it is imperative to elucidate the roles that different microbiota play in the maintenance of human health and in the development of diseases. To this end, novel statistical methods are sorely needed to translate the massive amount of newly generated microbiome data into scientific discovery. This workshop will focus on methods to address emerging challenges in the analysis of such data. It will bring together international experts in this important field of research to advance our understanding of the methods and tools which can be effectively applied to address common issues that arise in the analysis of human microbiome data.
The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).
