103 Animal Science Resource Center
MUII Dissertation Defense-Lynsey Whitacre
Alternative Applications of Whole Genome De Novo Assembly in Animal Genomics
Improvements in whole genome sequencing technologies have allowed substantial increases in the amount of data that can be generated on a single individual. This has facilitated many de novo genome assembly projects in the animal sciences. The overarching goal of de novo assembly is to overlap sequencing reads to construct contiguous sequences, also known as contigs or scaffolds, representing the genome. Once a high quality de novo assembly is constructed, it is often used to determine variation in the genome or simply as a reference for future resequencing projects. However, the nature of de novo assembly algorithms lends the method to contribute information about other characteristics of an animal’s genome. The research presented in this dissertation aims to maximize the use of de novo assemblies from both RNA and DNA sequencing to answer questions about animal genomics in the absence of other established genomics or bioinformatics tools designated for that purpose. These questions include detection of commensal and parasitic organisms in cattle, runs of homozygosity pertaining to a genetic defect in water buffalo, and population-level and species-level variation in a threatened catfish.
CE706 Clinical Support and Education Building
MUII Dissertation Defense- Rhonda Archie
Information Technology (IT) Interconnectivity in a Rural Health Setting: A Conceptual Model
Current and past developments in Health (HIT) systems in rural settings have focused on the use of electronic health records by health professionals. These systems were conducted in standalone mode, or coupled with the integration of HIT systems of two or more other HIT systems. In addition, this lack of interconnectivity involved diminished coordination in information sharing among the systems (Bahensky 2008; McCullough 2009). Grossman (2006) and Kevin (2008) investigated the state of HIT systems’ interconnectivity using networks in a rural health setting to promote sharing and communication of HIT systems. The authors found scanty information and limited initiatives to interconnect HIT systems. According to these authors, rural health settings face problems of purchase decision and implementation of HIT incorporating interconnectivity of the systems. More recent studies allude to the importance and need for rural health settings to foster interconnectivity among existing systems (Moidduddin 2007; Blumenthal 2009). Thus, there is also a need for using HIT systems that are proficient HIT interconnectivity systems. Brodkin (2007) noted enabling the HIT systems to communicate and share information effectively and efficiently can be achieved through HIT interconnectivity of existing systems for both rural and urban settings. The phenomenon of “HIT interconnectivity” being investigated in this study is not well understood in the literature (Trimmer, Pumphrey, and Wiggins, 2002). The proposed “Six-Factor Information Technology Interconnectivity (SFITI) Model” that rural health clinic administrators can use during HIT decision-making processes to generate new solutions provides an innovative approach. In addition, the proposed “Information Technology Interconnectivity in Rural Health (ITIRH) Survey” will serve as a new instrument for conducting research associated with HIT systems’ need, diffusion, implementation, reflection, interconnectivity, and environment. The proposed SFITI model and proposed ITIRH survey, novel forms of HIT innovation, are being developed. The purpose is to improve the structure and dynamics of HIT systems’ efficiency, clinical effectiveness, cost effectiveness, and productivity in rural health settings.
240 Naka Hall
MUII Comprehensive Exam- Saad Khan
Comparison of histone modifications across species
A cell’s identity is determined by distinct sets of genes that are expressed at a given point of time. An important factor in determining which set of genes are expressed is the cells epigenome. Epigenomes are known to play an important role across all eukaryotic species in gene regulation, genome integrity, dosage compensation and development. Histone modifications are an important component of the epigenome. These histone marks are post translational modifications that take place on the n-terminal tails of histone proteins. The growth of complex and heterogeneous epigenomic data sets has led to the development of “Comparative Epigenomics”. Comparative epigenomics has three dimensions namely ‘comparison of the epigenome of same individual over a period of time or different tissue types’, ‘comparison between different individuals of the same species’, and ‘comparison of epigenomes of different species’. Comparison of histone modification across time-points, individuals or species is crucial in understanding how epigenomes evolve over time. In this work we propose informatics approaches to address three specific aims: 1) Understand how histone modifications evolve between species and across different tissues. 2) Study the factors that contribute/drive change in epigenome across species. 3) How epigenomes change across various cancer subtypes and what factors drive that change. Lastly, we will use comparative epigenomic features to better predict enhancer promoter looping. A better understanding of how these histone modifications co-appear and evolve with respect to sequence across species would help in coming up with better models of transcriptional network evolution.
2206A Student Center
White Mothers’ Willingness to Share Personal Health Data: Survey Results and Future Research Implication
The objective of this research is to understand white mothers’ willingness to share their personal health data (PHD). Studies have shown that participants are willing to share their data when there is a benefit to do so, and when their data are kept private and secure. We recruited a representative sample of white mothers with children without disabilities from an opt-in panel to assess their willingness to share their PHD. We surveyed these mothers on their attitudes and beliefs and trust in data sharing, data sharing thru devices, internet use and interest in future research, and questions related to caregivers and their children. 15 questions out of 51 in the survey were selected for analysis. We found that mothers’ general health was associated with mothers’ desire to keep their PHD anonymous. The income level, health status of the youngest child, and use of internet were associated with respondents’ use of patient portal. The age of child was associated with mothers’ willingness to share their health information anonymously with researchers. We analyzed the implication of these findings on the ongoing project and for future research..
2206A Student Center
Characterizing Physician EMR Workflow With Clustering and Hilbert Space Filling Curve Visualizations
Understanding sequences of events is paramount to developing a picture of how clinicians interact with other clinicians, patients, and Electronic Medical Records (EMR). Common methods of assessing clinical workflow include qualitative methods such as video recording, direct observations, or directed user experience testing in a controlled environment. Studies such as these are designed to help understand traditional workflow concepts such as time and motion efficiency, interpersonal communication, and information needs. Applications for EMR workflow include measuring productivity to help target training, and dynamic EMR experiences based on predicted actions. Computational, or quantitative, methods can also be applied, such as sequential pattern mining, clustering, workflow mining, and graph-based mining. Visualization techniques can also help in discovering patterns; however, the combination of longitudinal and multi-variate data can be challenging to visualize. Approaches to these challenges generally favor the use of motion charts to represent the passage of time while visualized elements represent other attributes and change over time. In this talk, I will present a clustering methodology for grouping similar workflow patterns and visualizing workflow patterns efficiently through the use of space filling curves, such as the Hilbert Curve.
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