01840nas a2200229 4500008004100000245013200041210006900173260002700242520109800269653001801367653001101385653002801396653000801424100001901432700002001451700001901471700001801490700002001508700001601528700002601544856004001570 2012 eng d00aLocalized Deconvolution: Characterizing NMR-based Metabolomics Spectroscopic Data using Localized High-throughput Deconvolution0 aLocalized Deconvolution Characterizing NMRbased Metabolomics Spe aLas Vegas, Nevada, USA3 aThe 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 average relative quantification error by 88%. When applied to a 1H metabolomics study, the cross-validation metric, Q2, improved 16% by reducing within group variability. This increase in accuracy leads to additional computing costs that are overcome by translating the algorithm to the mapreduce design paradigm.10adeconvolution10aHadoop10alocalized deconvolution10aNMR1 aAnderson, Paul1 aRanabahu, Ajith1 aMahle, Deirdre1 aReo, Nicholas1 aRaymer, Michael1 aSheth, Amit1 aDelRaso, Nicholas, J. uhttp://knoesis.wright.edu/node/128400548nas a2200157 4500008004100000245009000041210006900131100001900200700002300219700002400242700002600266700002200292700001600314700002000330856004000350 2010 eng d00aCloud-based Map-Reduce Architecture for Nuclear Magnetic Resonance based Metabolomics0 aCloudbased MapReduce Architecture for Nuclear Magnetic Resonance1 aAnderson, Paul1 aManjunatha, Ashwin1 aRanabahu, Ajith, H.1 aDelRaso, Nicholas, J.1 aReo, Nicholas, V.1 aSheth, Amit1 aRaymer, Michael uhttp://knoesis.wright.edu/node/233602105nas a2200157 4500008004100000245009900041210006900140520158300209100001701792700001501809700001901824700002001843700002601863700001801889856004001907 2009 eng d00aCharacterization of 1H NMR Spectroscopic Data and the Generation of Synthetic Validation Sets.0 aCharacterization of 1H NMR Spectroscopic Data and the Generation3 aMotivation: Common contemporary practice within the nuclear magnetic resonance (NMR) metabolomics community is to evaluate and validate novel algorithms on empirical data or simplified simulated data. Empirical data captures the complex characteristics of experimental data, but the optimal or most correct analysis is unknown a priori; therefore, researchers are forced to rely on indirect performance metrics, which are of limited value. In order to achieve fair and complete analysis of competing techniques more exacting metrics are required. Thus, metabolomics researchers often evaluate their algorithms on simplified simulated data with a known answer. Unfortunately, the conclusions obtained on simulated data are only of value if the data sets are complex enough for results to generalize to true experimental data. Ideally, synthetic data should be indistinguishable from empirical data, yet retain a known best analysis. Results: We have developed a technique for creating realistic synthetic metabolomics validation sets based on NMR spectroscopic data. The validation sets are developed by characterizing the salient distributions in sets of empirical spectroscopic data. Using this technique, several validation sets are constructed with a variety of characteristics present in real data. A case study is then presented to compare the relative accuracy of several alignment algorithms using the increased precision afforded by these synthetic data sets. Availability: These data sets are available for download at http://birg.cs.wright.edu/nmr_synthetic_data_sets.1 aDoom, Travis1 aKelly, Ben1 aAnderson, Paul1 aRaymer, Michael1 aDelRaso, Nicholas, J.1 aReo, Nicholas uhttp://knoesis.wright.edu/node/104800503nas a2200145 4500008004100000245009500041210006900136100001700205700002600222700001700248700001400265700002000279700001800299856004000317 2008 eng d00aDose and Time Response Metabolomic Analyses of a-Napthylisothiocyanate Toxicity in the Rat0 aDose and Time Response Metabolomic Analyses of aNapthylisothiocy1 aWestrick, M.1 aDelRaso, Nicholas, J.1 aNeuforth, A.1 aMahle, D.1 aRaymer, Michael1 aReo, Nicholas uhttp://knoesis.wright.edu/node/241000508nas a2200145 4500008004100000245009800041210007100139100002600210700001700236700002000253700001400273700001800287700001700305856004000322 2008 eng d00aDose and Time Response Metabolomic Analyses of Î±-Napthylisothiocyanate Toxicity in the Rat0 aDose and Time Response Metabolomic Analyses of Î±Napthylisothioc1 aDelRaso, Nicholas, J.1 aWestrick, M.1 aRaymer, Michael1 aMahle, D.1 aReo, Nicholas1 aNeuforth, A. uhttp://knoesis.wright.edu/node/157500426nas a2200121 4500008004100000245007600041210006900117100001400186700002000200700002600220700001800246856004000264 2008 eng d00aGaussian Binning for Processing NMR Spectroscopic Data for Metabolomics0 aGaussian Binning for Processing NMR Spectroscopic Data for Metab1 aErson, P.1 aRaymer, Michael1 aDelRaso, Nicholas, J.1 aReo, Nicholas uhttp://knoesis.wright.edu/node/146300483nas a2200109 4500008004100000245017100041210006900212100001400281700002000295700001800315856004000333 2008 eng d00aStatistical Population Thresholding: A novel non-linear thresholding method for peak and baseline selection in biological spectra containing thermally generated noise0 aStatistical Population Thresholding A novel nonlinear thresholdi1 aHomer, D.1 aRaymer, Michael1 aReo, Nicholas uhttp://knoesis.wright.edu/node/175700509nas a2200157 4500008004100000245007800041210006900119100002000188700001400208700002600222700001400248700001700262700001800279700001400297856004000311 2008 eng d00aA Time and Dose Response Metabonomics Study of D-serine Toxicity in Rats.0 aTime and Dose Response Metabonomics Study of Dserine Toxicity in1 aRaymer, Michael1 aCouch, W.1 aDelRaso, Nicholas, J.1 aErson, P.1 aNeuforth, A.1 aReo, Nicholas1 aMahle, D. uhttp://knoesis.wright.edu/node/146400525nas a2200145 4500008004100000245012000041210006900161100001400230700001700244700001400261700001800275700002600293700002000319856004000339 2007 eng d00aComparison of Statistical Techniques for the Analysis of Metabolic Toxicological Data Derived from NMR Spectroscopy0 aComparison of Statistical Techniques for the Analysis of Metabol1 aKelly, B.1 aDoom, Travis1 aErson, P.1 aReo, Nicholas1 aDelRaso, Nicholas, J.1 aRaymer, Michael uhttp://knoesis.wright.edu/node/171800520nas a2200145 4500008004100000245011500041210006900156100002000225700001800245700001400263700001700277700001400294700002600308856004000334 2007 eng d00aA proposed statistical protocol for the analysis of metabolic toxicological data derived from NMR spectroscopy0 aproposed statistical protocol for the analysis of metabolic toxi1 aRaymer, Michael1 aReo, Nicholas1 aErson, P.1 aDoom, Travis1 aKelly, B.1 aDelRaso, Nicholas, J. uhttp://knoesis.wright.edu/node/171600524nas a2200145 4500008004100000245011600041210006900157100001700226700002000243700001800263700001700281700002600298700001400324856004000338 2006 eng d00aCombined Urine and Plasma Metabolomic Analysis of alpha-Napthylisothiocyanate (ANIT) Liver Toxicity in the Rat.0 aCombined Urine and Plasma Metabolomic Analysis of alphaNapthylis1 aWestrick, M.1 aRaymer, Michael1 aReo, Nicholas1 aNeuforth, A.1 aDelRaso, Nicholas, J.1 aMahle, D. uhttp://knoesis.wright.edu/node/1745