Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 5 of 5
Full-Text Articles in Entire DC Network
Metabolomics Characterization Of U.S. And Japanese F-15 And C-130 Flight Line Crews Exposed To Jet Fuel Volatile Organic Compounds And Aerosols, Nicholas J. Delraso, David Mattie, Asao Kobayashi, Stephen W. Mitchell, Scott Dillard, Michael L. Raymer, Isaie Sibomana, Nicholas V. Reo
Metabolomics Characterization Of U.S. And Japanese F-15 And C-130 Flight Line Crews Exposed To Jet Fuel Volatile Organic Compounds And Aerosols, Nicholas J. Delraso, David Mattie, Asao Kobayashi, Stephen W. Mitchell, Scott Dillard, Michael L. Raymer, Isaie Sibomana, Nicholas V. Reo
Computer Science and Engineering Faculty Publications
Air and ground crews transfer a significant amount of jet fuel, and as a result of transfers, breathe its volatile emission from residues. Working on the flight line also exposes maintainers to exhaust from the jet fuel as engines are tested or run before and after flight. Since little is known concerning level of exposure and the corresponding biological response associated with human jet fuel exposure, nuclear magnetic resonance (NMR)-based metabolomics analysis of human urine was utilized for characterization of metabolite profiles of flight line personnel for potential biomarker discovery. This project was a collaborative research effort between the US …
Biomarkers Of Fatigue: Metabolomics Profiles Predictive Of Cognitive Performance, Nicholas J. Delraso, Deirdre A. Mahle, John J. Schlager, Donald L. Harville, Scott R. Chaiken, Danelle K. Roddy, Mari Chamberlain, Paul E. Anderson, Nicholas V. Reo, Michael L. Raymer, Isaie Sibomana
Biomarkers Of Fatigue: Metabolomics Profiles Predictive Of Cognitive Performance, Nicholas J. Delraso, Deirdre A. Mahle, John J. Schlager, Donald L. Harville, Scott R. Chaiken, Danelle K. Roddy, Mari Chamberlain, Paul E. Anderson, Nicholas V. Reo, Michael L. Raymer, Isaie Sibomana
Computer Science and Engineering Faculty Publications
Cognitive performance and fatigue are well known to be inversely related. Continuous and sustained actions in operational environments typically lead to reduced sleep normally required to perform optimally. These operational environments subject the warfighter to intense physical and mental exertion. Because fatigue continues to be an occupational hazard, leading to cognitive defects in performance, there has been a recognized need for real-time detection technologies that minimize fatigue-induced mishaps. I the current study, 23 subjects were subjected to 36h of sleep deprivation and cognitive psychomotor vigilance and automated neuropsychological assessment metric tests were conducted over the last 24 h of sleep …
Localized Deconvolution: Characterizing Nmr-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution, Paul E. Anderson, Ajith H. Ranabahu, Deirdre A. Mahle, Nicholas V. Reo, Michael L. Raymer, Amit P. Sheth, Nicholas J. Delraso
Localized Deconvolution: Characterizing Nmr-Based Metabolomics Spectroscopic Data Using Localized High-Throughput Deconvolution, Paul E. Anderson, Ajith H. Ranabahu, Deirdre A. Mahle, Nicholas V. Reo, Michael L. Raymer, Amit P. Sheth, Nicholas J. Delraso
Kno.e.sis Publications
The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. Standard quantification techniques attempt to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition. These techniques fail to account for adjacent signals which can lead to drastic quantification errors. Attempts at full spectrum deconvolution have been limited in adoption and development due to the computational resources required. Herein, we develop a novel localized deconvolution algorithm for general purpose quantification of NMR-based metabolomics studies. Localized deconvolution decreases average absolute quantification error by 97% and …
Identifying And Implementing The Underlying Operators For Nuclear Magnetic Resonance Based Metabolomics Data Analysis, Ashwin Manjunatha, Ajith H. Ranabahu, Paul E. Anderson, Amit P. Sheth
Identifying And Implementing The Underlying Operators For Nuclear Magnetic Resonance Based Metabolomics Data Analysis, Ashwin Manjunatha, Ajith H. Ranabahu, Paul E. Anderson, Amit P. Sheth
Kno.e.sis Publications
The science of metabolomics is a relatively young field that requires intensive signal processing and multivariate data analysis for interpretation of experimental results. The lack of integration and standardization for metabolomics compounded by the complexity of the experimental data has lead to a fragmented research community. While efforts have been undertaken to approach these problems, the efforts to develop a set of standards for reporting processing and analysis procedures has stalled.
In this paper, we propose a set of fundamental operators for nuclear magnetic resonance(NMR) based metabolomics. These operators are implementation independent, and can be used to easily and precisely …
Getting Code Near The Data: A Study Of Generating Customized Data Intensive Scientific Workflows With Domain Specific Language, Ashwin Manjunatha, Ajith Harshana Ranabahu, Paul E. Anderson, Amit P. Sheth
Getting Code Near The Data: A Study Of Generating Customized Data Intensive Scientific Workflows With Domain Specific Language, Ashwin Manjunatha, Ajith Harshana Ranabahu, Paul E. Anderson, Amit P. Sheth
Kno.e.sis Publications
The amount of data produced in modern biological experiments such as Nuclear Magnetic Resonance (NMR) analysis far exceeds the processing capability of a single machine. The present state-of-the-art is taking the ”data to code”, the philosophy followed by many of the current service oriented workflow systems. However this is not feasible in some cases such as NMR data analysis, primarily due to the large scale of data.
The objective of this research is to bring ”code to data”, preferred in the cases when the data is extremely large. We present a DSL based approach to develop customized data intensive scientific …