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David S. Wishart

Researcher at University of Alberta

Publications -  564
Citations -  93527

David S. Wishart is an academic researcher from University of Alberta. The author has contributed to research in topics: Metabolomics & Medicine. The author has an hindex of 108, co-authored 523 publications receiving 76652 citations. Previous affiliations of David S. Wishart include La Trobe University & International Agency for Research on Cancer.

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MetATT: a web-based metabolomics tool for analyzing time-series and two-factor datasets.

TL;DR: MetATT, a web-based tool for time-series and two-factor metabolomic data analysis, is introduced, which offers a number of complementary approaches including 3D interactive principal component analysis, two-way heatmap visualization, three-way ANOVA, ANOVA-simultaneous component analysis and multivariate empirical Bayes time- series analysis.
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Validation of metabolomic models for prediction of early-onset preeclampsia.

TL;DR: Confirmatory evidence is found that first-trimester metabolomic biomarkers can predict future development of early PE and area under the receiver operator characteristic curve (AUC), 95% confidence interval, sensitivity, and specificity of the biomarker models were derived.
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Learning to predict cancer-associated skeletal muscle wasting from 1H-NMR profiles of urinary metabolites

TL;DR: 1H-NMR analysis of a single random urine sample may be a fast, cheap, safe and inexpensive tool to screen and monitor muscle loss, and that useful classifiers for predicting related metabolic conditions are possible with the methodology presented.
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MovieMaker: a web server for rapid rendering of protein motions and interactions

TL;DR: MovieMaker is a web server that allows short, downloadable movies of protein motions to be generated and uses a sophisticated superpositioning algorithm in conjunction with Cartesian coordinate interpolation to rapidly and automatically calculate the intermediate structures needed for many of its animations.
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Simulations of Interdigitated Electrode Interactions with Gold Nanoparticles for Impedance-Based Biosensing Applications

TL;DR: Using simulations of a point-of-care biosensor design, it was observed that gold nanoparticles bound closely to IDEs can lower the electric field magnitude between the digits of the electrode.