This is What a Wildcat Sounds Like!
A video showcasing the linguistic diversity of UK. We take pride in the unique gifting, talents, and voices that diversity brings to our campus and our community! This is what a Wildcat sounds like!
A video showcasing the linguistic diversity of UK. We take pride in the unique gifting, talents, and voices that diversity brings to our campus and our community! This is what a Wildcat sounds like!
Abstract: Recent research has revealed the essential role that microbial metabolites play in host-microbiome interactions. Although statistical and machine-learning methods have been employed to explore microbiome-metabolome interactions in multiview microbiome studies, most of these approaches focus solely on the prediction of microbial metabolites, which lacks biological interpretation. Additionally, existing methods face limitations in either prediction or inference due to small sample sizes and highly correlated microbes and metabolites. To overcome these limitations, we present a transfer-learning method that evaluates microbiome-metabolome interactions. Our approach efficiently utilizes information from comparable metabolites obtained through external databases or data-driven methods, resulting in more precise predictions of microbial metabolites and identification of essential microbes involved in each microbial metabolite. Our numerical studies demonstrate that our method enables a deeper understanding of the mechanism of host-microbiome interactions and establishes a statistical basis for potential microbiome-based therapies for various human diseases.
By Richard LeComte
LEXINGTON, Ky. – The University of Maine Alumni Association will honor D. Allan Butterfield, the University of Kentucky Alumni Association Endowed Professor of Biological Chemistry, with its 2023 Alumni Career Award.
A few photos from our 2023 Founder's Day event!
Second year MFA students who will be graduating in May will read from their theses.