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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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Journal ArticleDOI

CFM-ID 4.0 – a web server for accurate MS-based metabolite identification

TL;DR: CFM-ID 4.0 as discussed by the authors is an online tool for predicting, annotating and interpreting tandem mass (MS/MS) spectra of small molecules, specifically designed to assist researchers pursuing studies in metabolomics, exposomics and analytical chemistry.
Journal ArticleDOI

In Silico Drug Exploration and Discovery Using DrugBank

TL;DR: The intent of this unit is to give readers some introduction into the field of cheminformatics (the study of chemical information) and to show how chemin Formatics can be seamlessly integrated into theField of bioinformatics.
Journal ArticleDOI

Urinary Metabolomics around Parturition Identifies Metabolite Alterations in Dairy Cows Affected Postpartum by Lameness: Preliminary Study

TL;DR: Results showed that urine metabotyping can be used to identify cows at risk of lameness and to better characterize lameness from the metabolic prospective, however, caution should be taken in interpretation of the data presented because of the low number of replicates.
Journal ArticleDOI

Experimental and computational study of the interaction of novel colchicinoids with a recombinant human αI/βI-tubulin heterodimer

TL;DR: The binding free energies on human tubulin of selected colchicine and thiocolchicines compounds were determined using a series of experiments that measured the affinity of the compound on a synthetically expressed and purified tubulin protein using a spectrofluorometric technique.
Book ChapterDOI

Automated Tools for the Analysis of 1D-NMR and 2D-NMR Spectra.

TL;DR: This chapter describes the step-by-step preparation of biofluid samples along with the required protocols for acquiring optimal spectra for automated NMR metabolomics analysis and discusses the use of three common tools for (semi-) automated profiling, and annotation of 1D- and 2D-NMR spectra ofBiofluids.