Open Access. Powered by Scholars. Published by Universities.®

Biomedical Engineering and Bioengineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 2 of 2

Full-Text Articles in Biomedical Engineering and Bioengineering

Direct Quantification Of Deubiquitinating Enzyme Activity In Single Intact Cells, Nora Safabakhsh Aug 2018

Direct Quantification Of Deubiquitinating Enzyme Activity In Single Intact Cells, Nora Safabakhsh

LSU Doctoral Dissertations

Challenges in drug efficacy occur during the treatment of most types of cancer due to the heterogeneity of the tumor microenvironment. This has led to the development of personalized medicine. Due to the clinical success of the proteasome inhibitors Bortezomib and Carfilzomib in treatment of multiple myeloma, interest has shifted towards molecularly-targeted chemotherapeutics for ubiquitin-proteasome system (UPS). Deubiquitinating enzymes (DUBs) are an essential part of this pathway which have been found to promote Bortezomib resistance in multiple myeloma patients. Unfortunately, there is a lack of specific, high throughput biochemical assays to characterize DUB activity in patient samples before and after …


A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das Jun 2018

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 …