Medicine and Health Sciences Commons^™

Imputation Of Plasma Lipid Species To Facilitate Integration Of Lipidomic Datasets, Aleksandar Dakic, Jingqin Wu, Tingting Wang, Kevin Huynh, Natalie Mellett, Thy Duong, Habtamu B. Beyene, Dianna J. Magliano, Joanne E. Curran, John Blangero

School of Medicine Publications and Presentations

Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less …

Integrating Data Types To Estimate Spatial Patterns Of Avian Migration Across The Western Hemisphere, Timothy D. Meehan, Sarah P. Saunders, William V. Deluca, Nicole L. Michel, Joanna Grand, Jill L. Deppe, Miguel F. Jimenez, Erika J. Knight, Nathaniel E. Seavy, Melanie A. Smith, Lotem Taylor, Chad Witko, Michael E. Akresh, David R. Barber, Erin M. Bayne, James C. Beasley, Jerrold L. Belant, Richard O. Bierregaard, Keith L. Bildstein, Than J. Boves, John N. Brzorad, Steven P. Campbell, Antonio Celis-Murillo, Hilary A. Cooke, Robert Domenech, Laurie Goodrich, Elizabeth A. Gow, Aaron Haines, Michael T. Hallworth, Jason M. Hill, Amanda E. Holland, Scott Jennings, Roland Kays, Tommy King, Stuart A. Mackenzie, Peter P. Marra, Rebecca A. Mccabe, Kent P. Mcfarland, Michael J. Mcgrady, Ron Melcer, D. Ryan Norris, Russell E. Norvell, Olin E. Rhodes, Christopher C. Rimmer, Amy L. Scarpignato, Adam Shreading, Jesse L. Watson, Chad R. Wilsey

USDA Wildlife Services: Staff Publications

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence …

The Population Health Outcomes And Information Exchange (Phoenix) Program - A Transformative Approach To Reduce The Burden Of Chronic Disease, Steven J. Korzeniewski, Carla Bezold, Jason T. Carbone, Shooshan Danagoulian, Bethany Foster, Dawn Misra, Maher M. El-Masri, Dongxiao Zhu, Robert Welch, Lauren Meloche, Alex B. Hill, Phillip Levy

Urban Studies and Planning Faculty Research Publications

This concept article introduces a transformative vision to reduce the population burden of chronic disease by focusing on data integration, analytics, implementation and community engagement. Known as PHOENIX (The Population Health OutcomEs aNd Information EXchange), the approach leverages a state level health information exchange and multiple other resources to facilitate the integration of clinical and social determinants of health data with a goal of achieving true population health monitoring and management. After reviewing historical context, we describe how multilevel and multimodal data can be used to facilitate core public health services, before discussing the controversies and challenges that lie ahead.

Research Data Management From The Stem Perspective: Reproducibility, Data Reuse, Data Integration, Melissa D. Clarkson

Institute for Biomedical Informatics Presentations

This presentation highlights three big ideas in STEM data management:

• Reproducibility requires scripted pipelines
• Data reuse requires metadata and documentation
• Data integration requires use of standards

It also provides an overview of the FAIR principles for research data management.

Temporal-Spatial Heterogeneity In Animal-Environment Contact: Implications For The Exposure And Transmission Of Pathogens, Shi Chen, Michael W. Sanderson, Brad J. White, David E. Armine, Cristina Lanzas

Faculty Publications and Other Works -- Biomedical and Diagnostic Sciences

Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental …