Life Sciences Commons^™

Functional, Proteomic And Bioinformatic Analyses Of Nrf2- And Keap1- Null Skeletal Muscle, Lie Gao, Vikas Kumar, Neetha Nanoth Vellichirammal, Song-Young Park, Tara L. Rudebush, Li Yu, Won-Mok Son, Elizabeth J. Pekas, Ahmed M. Wafi, Juan Hong, Peng Xiao, Chittibabu Guda, Han-Jun Wang, Harold D. Scultz, Irving H. Zucker

Health and Kinesiology Faculty Publications

Key points

• Nrf2 is a master regulator of endogenous cellular defences, governing the expression of more than 200 cytoprotective proteins, including a panel of antioxidant enzymes.
• Nrf2 plays an important role in redox haemostasis of skeletal muscle in response to the increased generation of reactive oxygen species during contraction.
• Employing skeletal muscle-specific transgenic mouse models with unbiased-omic approaches, we uncovered new target proteins, downstream pathways and molecular networks of Nrf2 in skeletal muscle following Nrf2 or Keap1 deletion.
• Based on the findings, we proposed a two-way model to understand Nrf2 function: a tonic effect through a Keap1-independent mechanism under basal …

A Dynamic Run-Profile Energy-Aware Approach For Scheduling Computationally Intensive Bioinformatics Applications, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

High Performance Computing (HPC) resources are housed in large datacenters, which consume exorbitant amounts of energy and are quickly demanding attention from businesses as they result in high operating costs. On the other hand HPC environments have been very useful to researchers in many emerging areas in life sciences such as Bioinformatics and Medical Informatics. In an earlier work, we introduced a dynamic model for energy aware scheduling (EAS) in a HPC environment; the model is domain agnostic and incorporates both the deadline parameter as well as energy parameters for computationally intensive applications. Our proposed EAS model incorporates 2-phases. In …

A Novel Approach To Identify Shared Fragments In Drugs And Natural Products, Ashkay Balasubramanya, Ishwor Thapa, Dhundy Raj Bastola, Dario Ghersi

Interdisciplinary Informatics Faculty Proceedings & Presentations

Fragment-based approaches have now become an important component of the drug discovery process. At the same time, pharmaceutical chemists are more often turning to the natural world and its extremely large and diverse collection of natural compounds to discover new leads that can potentially be turned into drugs. In this study we introduce and discuss a computational pipeline to automatically extract statistically overrepresented chemical fragments in therapeutic classes, and search for similar fragments in a large database of natural products. By systematically identifying enriched fragments in therapeutic groups, we are able to extract and focus on few fragments that are …

A Noise Reducing Sampling Approach For Uncovering Critical Properties In Large Scale Biological Networks, Karthik Duraisamy, Kathryn Dempsey Cooper, Hesham Ali, Sanjukta Bhowmick

Interdisciplinary Informatics Faculty Proceedings & Presentations

A correlation network is a graph-based representation of relationships among genes or gene products, such as proteins. The advent of high-throughput bioinformatics has resulted in the generation of volumes of data that require sophisticated in silico models, such as the correlation network, for in-depth analysis. Each element in our network represents expression levels of multiple samples of one gene and an edge connecting two nodes reflects the correlation level between the two corresponding genes in the network according to the Pearson correlation coefficient. Biological networks made in this manner are generally found to adhere to a scale-free structural nature, that …

An Improved String Composition Method For Sequence Comparison, Guoquing Lu, Shunpu Zhang, Xiang Fang

Biology Faculty Publications

Background: Historically, two categories of computational algorithms (alignment-based and alignment-free) have been applied to sequence comparison–one of the most fundamental issues in bioinformatics. Multiple sequence alignment, although dominantly used by biologists, possesses both fundamental as well as computational limitations. Consequently, alignment-free methods have been explored as important alternatives in estimating sequence similarity. Of the alignment-free methods, the string composition vector (CV) methods, which use the frequencies of nucleotide or amino acid strings to represent sequence information, show promising results in genome sequence comparison of prokaryotes. The existing CV-based methods, however, suffer certain statistical problems, thereby underestimating the amount of evolutionary …

On The Tradeoff Between Speedup And Energy Consumption In High Performance Computing – A Bioinformatics Case Study, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

High Performance Computing has been very useful to researchers in the Bioinformatics, Medical and related fields. The bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Automated techniques such as DNA sequencers, DNA microarrays & others are continually growing the dataset that is stored in large public databases such as GenBank and Protein DataBank. Most methods used for analyzing genetic/protein data have been found to be extremely computationally intensive, providing motivation for the use of powerful computers or systems with high throughput characteristics. In this paper, we provide a …