Biomedical Engineering and Bioengineering Commons^™

A Discrete-Event Simulation Approach For Modeling Human Body Glucose Metabolism, Buket Aydas

Theses and Dissertations

This dissertation describes CarbMetSim (Carbohydrate Metabolism Simulator), a discrete-event simulator that tracks the blood glucose level of a person in response to a timed sequence of diet and exercise activities. CarbMetSim implements broader aspects of carbohydrate metabolism in human beings with the objective of capturing the average impact of various diet/exercise activities on the blood glucose level. Key organs (stomach, intestine, portal vein, liver, kidney, muscles, adipose tissue, brain and heart) are implemented to the extent necessary to capture their impact on the production and consumption of glucose. Key metabolic pathways (glucose oxidation, glycolysis and gluconeogenesis) are accounted for by …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …

Transcriptomics To Develop Biochemical Network Models In Cyanobacteria, Bridget E. Hegarty, Jordan Peccia, Ratanachat Racharaks

Yale Day of Data

Through targeted genetic manipulations guided by network modeling, we will create a flexible, cyanobacteria-based platform for the production of biofuel-precursors and valuable chemical products. To build gene-metabolite predictive models, we have characterized Synecococcus elongatus sp. UTEX 2973’s (henceforth, UTEX 2973) gene expression and metabolite production under a number of environmental conditions.

Asd Biomarker Detection On Fmri Images: Feature Learning With Data Corruptions By Analyzing Deep Neural Network Classifier Outcomes, Xiaoxiao Li 6984086

Yale Day of Data

Autism spectrum disorder (ASD) is a complex neurological and developmental disorder. It emerges early in life and is generally associated with lifelong disability. Finding the biomarkers associated with ASD is extremely helpful to understand the underlying roots of the disorder and find more targeted treatment. Previous studies suggested brain activations are abnormal in ASDs, hence functional magnetic resonance imaging (fMRI) has been used to identify ASD. In this work we addressed the problem of interpreting reliable biomarkers in classifying ASD vs. control; therefore, we proposed a 2-step pipeline: 1) classifying ASD and control fMRI images by deep neural network, and …