The University of Kentucky College of Public Health and the department of Epidemiology & Environmental Health (EEH) is hosting a faculty candidate, Dr. Yike Shen, to give a presentation on "High dimensional exposures, multi-omics, and machine learning in environmental health" on Monday, October 24th, from 4:00pm - 5:00pm in room 207 at Research Building 1 or virtual (Zoom details are below).
Dr. Shen is a postdoctoral research scientist at Columbia University and her research focus includes: environmental health data science, microbiome, machine learning, high-dimensional data analysis, bioinformatics, multi-omics, and environmental exposure.
All CPH faculty and staff are invited.
Abstract:
High-dimensional data in environmental health sciences present unprecedented challenges and opportunities. In this presentation, Dr. hen will share her research spanning from microbiome epidemiology to precision computational environmental health.
Humans are exposed to a myriad of environmental pollutants (e.g., pharmaceuticals and personal care products, metals, pesticides, etc.) every day. Individual or mixtures of pollutants may relate to changes in the human gut microbiome and further impact human health.
Dr. Shen will share her work in microbiome epidemiology studying the influences of environmental metals on the pediatric gut microbiome in a healthy gestation cohort. Altering the gut microbiome is not the only way environmental pollutants can impact human health. Epigenome-wide DNA methylation data capture collective exposures and can serve as biomarkers for human health.
Dr. Shen’s new autoencoder deep learning survival analysis model achieved state-of-the-art coronary heart disease prediction accuracy in marginalized American Indian communities with disproportionally high coronary heart disease prevalence. Accurate prediction of contaminant processes in the environment is a critical step in chemical risk assessment.
Dr. Shen will discuss our successful prediction of hundreds of pesticide dissipation half-life intervals in plants using machine learning models.
Finally, inspired by knowledge-driven discovery initiatives, Dr. Shen will talk our recent work constructing a knowledge graph towards open science and knowledge-driven discovery for cohort studies. In the future, I will keep integrating high-dimensional exposures, multi-omics, and health outcomes to advance environmental health science
Learn more about Dr. Shen's research here.
Zoom Link
Zoom Password (if required): 615639
