David J. Vocadlo

16.7k total citations · 4 hit papers
200 papers, 11.2k citations indexed

About

David J. Vocadlo is a scholar working on Molecular Biology, Organic Chemistry and Physiology. According to data from OpenAlex, David J. Vocadlo has authored 200 papers receiving a total of 11.2k indexed citations (citations by other indexed papers that have themselves been cited), including 161 papers in Molecular Biology, 143 papers in Organic Chemistry and 47 papers in Physiology. Recurrent topics in David J. Vocadlo's work include Carbohydrate Chemistry and Synthesis (142 papers), Glycosylation and Glycoproteins Research (130 papers) and Lysosomal Storage Disorders Research (44 papers). David J. Vocadlo is often cited by papers focused on Carbohydrate Chemistry and Synthesis (142 papers), Glycosylation and Glycoproteins Research (130 papers) and Lysosomal Storage Disorders Research (44 papers). David J. Vocadlo collaborates with scholars based in Canada, United Kingdom and United States. David J. Vocadlo's co-authors include G.J. Davies, Matthew S. Macauley, Scott A. Yuzwa, Stephen G. Withers, Keith A. Stubbs, Xiaoyang Shan, T.M. Gloster, Brian L. Mark, Garrett E. Whitworth and Keith Vosseller and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

David J. Vocadlo

193 papers receiving 11.1k citations

Hit Papers

A potent mechanism-inspired O-GlcNAcase inhibitor that bl... 2001 2026 2009 2017 2008 2001 2012 2003 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David J. Vocadlo Canada 58 9.1k 6.3k 2.7k 1.6k 1.5k 200 11.2k
Monica M. Palcic Canada 53 6.3k 0.7× 3.5k 0.6× 916 0.3× 664 0.4× 1.2k 0.8× 257 9.0k
Yukishige Ito Japan 55 9.5k 1.0× 7.9k 1.3× 1.2k 0.5× 343 0.2× 1.3k 0.8× 441 11.6k
Terry D. Butters United Kingdom 55 5.5k 0.6× 4.8k 0.8× 1.2k 0.4× 4.3k 2.7× 613 0.4× 189 10.4k
Yves Bourne France 48 5.4k 0.6× 1.8k 0.3× 650 0.2× 332 0.2× 787 0.5× 115 8.0k
Isabel Marzo Spain 48 8.5k 0.9× 998 0.2× 1.8k 0.6× 607 0.4× 168 0.1× 109 11.7k
Faustino Mollinedo Spain 55 5.8k 0.6× 979 0.2× 1.6k 0.6× 774 0.5× 286 0.2× 207 9.6k
Ronen Marmorstein United States 70 12.8k 1.4× 800 0.1× 969 0.4× 981 0.6× 267 0.2× 205 16.1k
L. Dorland Netherlands 43 4.4k 0.5× 1.6k 0.3× 786 0.3× 723 0.5× 363 0.2× 137 5.9k
Zhong‐Yin Zhang United States 54 6.6k 0.7× 1.1k 0.2× 3.4k 1.2× 678 0.4× 127 0.1× 188 9.5k
Hening Lin United States 54 5.8k 0.6× 769 0.1× 739 0.3× 1.1k 0.7× 194 0.1× 179 10.2k

Countries citing papers authored by David J. Vocadlo

Since Specialization
Citations

This map shows the geographic impact of David J. Vocadlo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David J. Vocadlo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Vocadlo more than expected).

Fields of papers citing papers by David J. Vocadlo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Vocadlo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David J. Vocadlo. The network helps show where David J. Vocadlo may publish in the future.

Co-authorship network of co-authors of David J. Vocadlo

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Vocadlo. A scholar is included among the top collaborators of David J. Vocadlo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David J. Vocadlo. David J. Vocadlo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Wu, Taiasean, Matthew G. Alteen, Carrie L. Partch, et al.. (2024). Protein-adaptive differential scanning fluorimetry using conformationally responsive dyes. Nature Biotechnology. 43(1). 106–113. 8 indexed citations
4.
Frick, Lukas, Johannes C. M. Schlachetzki, Andrea Armani, et al.. (2024). Direct and indirect regulation of β-glucocerebrosidase by the transcription factors USF2 and ONECUT2. npj Parkinson s Disease. 10(1). 192–192.
5.
Ashmus, Roger A., Matthew B. Nodwell, Yang Wang, et al.. (2024). A metabolic inhibitor blocks cellular fucosylation and enables production of afucosylated antibodies. Proceedings of the National Academy of Sciences. 121(27). e2314026121–e2314026121. 9 indexed citations
6.
Zhu, Sha, Yanping Zhu, Xi Chen, et al.. (2023). A Fixable Fluorescence‐Quenched Substrate for Quantitation of Lysosomal Glucocerebrosidase Activity in Both Live and Fixed Cells. Angewandte Chemie. 135(40). 1 indexed citations
7.
Ashmus, Roger A., Yang Wang, Dustin T. King, et al.. (2023). Potent and Selective Cell‐Active Iminosugar Inhibitors of Human α‐N‐Acetylgalactosaminidase (α‐NAGAL). Chemistry - A European Journal. 29(44). e202300982–e202300982. 1 indexed citations
9.
Zhu, Yanping, et al.. (2023). Axonal Transport of Lysosomes Is Unaffected in Glucocerebrosidase-Inhibited iPSC-Derived Forebrain Neurons. eNeuro. 10(10). ENEURO.0079–23.2023. 2 indexed citations
10.
Tomašič, Tihomir, Martina Gobec, Matthew G. Alteen, et al.. (2022). Discovery of a New Drug-like Series of OGT Inhibitors by Virtual Screening. Molecules. 27(6). 1996–1996. 5 indexed citations
11.
Meek, Richard W., et al.. (2022). The primary familial brain calcification-associated protein MYORG is an α-galactosidase with restricted substrate specificity. PLoS Biology. 20(9). e3001764–e3001764. 13 indexed citations
12.
Ashmus, Roger A., Dustin T. King, Arnaud Bordes, et al.. (2021). Structural variation of the 3-acetamido-4,5,6-trihydroxyazepane iminosugar through epimerization and C-alkylation leads to low micromolar HexAB and NagZ inhibitors. Organic & Biomolecular Chemistry. 20(3). 619–629. 3 indexed citations
13.
Meek, Richard W., et al.. (2021). Cryo-EM structure provides insights into the dimer arrangement of the O-linked β-N-acetylglucosamine transferase OGT. Nature Communications. 12(1). 6508–6508. 27 indexed citations
14.
Vickers, Chelsea, et al.. (2020). The structure of a family 110 glycoside hydrolase provides insight into the hydrolysis of α-1,3-galactosidic linkages in λ-carrageenan and blood group antigens. Journal of Biological Chemistry. 295(52). 18426–18435. 10 indexed citations
15.
Shan, Xiaoyang, et al.. (2020). Selective Fluorogenic β-Glucocerebrosidase Substrates for Convenient Analysis of Enzyme Activity in Cell and Tissue Homogenates. ACS Chemical Biology. 15(4). 824–829. 11 indexed citations
16.
Cecioni, Samy & David J. Vocadlo. (2017). Carbohydrate Bis-acetal-Based Substrates as Tunable Fluorescence-Quenched Probes for Monitoring exo -Glycosidase Activity. Journal of the American Chemical Society. 139(25). 8392–8395. 40 indexed citations
17.
Roth, Christian, Wendy A. Offen, G.R. Hemsworth, et al.. (2017). Structural and functional insight into human O-GlcNAcase. Nature Chemical Biology. 13(6). 610–612. 84 indexed citations
18.
Heinonen, Julia, Keith A. Stubbs, Christian Roth, et al.. (2016). Analysis of transition state mimicry by tight binding aminothiazoline inhibitors provides insight into catalysis by human O-GlcNAcase. Chemical Science. 7(6). 3742–3750. 30 indexed citations
19.
Sodi, Valerie L., Sakina Khaku, Raisa I. Krutilina, et al.. (2015). mTOR/MYC Axis Regulates O-GlcNAc Transferase Expression and O-GlcNAcylation in Breast Cancer. Molecular Cancer Research. 13(5). 923–933. 117 indexed citations
20.
Stubbs, Keith A., et al.. (2007). Small Molecule Inhibitors of a Glycoside Hydrolase Attenuate Inducible AmpC-mediated β-Lactam Resistance. Journal of Biological Chemistry. 282(29). 21382–21391. 101 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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