David E. James

39.1k total citations · 9 hit papers
370 papers, 29.3k citations indexed

About

David E. James is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, David E. James has authored 370 papers receiving a total of 29.3k indexed citations (citations by other indexed papers that have themselves been cited), including 285 papers in Molecular Biology, 122 papers in Cell Biology and 121 papers in Physiology. Recurrent topics in David E. James's work include Metabolism, Diabetes, and Cancer (170 papers), Adipose Tissue and Metabolism (98 papers) and Pancreatic function and diabetes (89 papers). David E. James is often cited by papers focused on Metabolism, Diabetes, and Cancer (170 papers), Adipose Tissue and Metabolism (98 papers) and Pancreatic function and diabetes (89 papers). David E. James collaborates with scholars based in Australia, United States and United Kingdom. David E. James's co-authors include Edward W. Kraegen, Jacqueline Stöckli, Sean J. Humphrey, Roland Govers, Donald J. Chisholm, Nia J. Bryant, Daniel J. Fazakerley, Georg Ramm, Hans J. Geuze and Robert C. Piper and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

David E. James

361 papers receiving 28.8k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Regulated transport of the glucose transporter GLUT4

2002 944 citations Nia J. Bryant, David E. James et al. profile →
Berberine, a Natural Plant Product, Activates AMP-Activated Protein Kinase With Beneficial Metabolic Effects in Diabetic and Insulin-Resistant States

2006 897 citations David E. James et al. profile →
Immuno-localization of the insulin regulatable glucose transporter in brown adipose tissue of the rat.

1991 781 citations David E. James et al. The Journal of Cell Biology profile →
Molecular cloning and characterization of an insulin-regulatable glucose transporter

1989 775 citations David E. James et al. profile →
Interleukin-6 Increases Insulin-Stimulated Glucose Disposal in Humans and Glucose Uptake and Fatty Acid Oxidation In Vitro via AMP-Activated Protein Kinase

2006 679 citations David E. James et al. profile →
Insulin-regulatable tissues express a unique insulin-sensitive glucose transport protein

1988 560 citations David E. James et al. profile →
Extracellular Vesicles Provide a Means for Tissue Crosstalk during Exercise

2018 483 citations Benjamin L. Parker, Kevin I. Watt et al. profile →
Protein Phosphorylation: A Major Switch Mechanism for Metabolic Regulation

2015 413 citations Sean J. Humphrey, David E. James et al. profile →
The aetiology and molecular landscape of insulin resistance

2021 399 citations David E. James, Jacqueline Stöckli et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
David E. James	19.3k	8.6k	7.7k	6.5k	3.1k	370	29.3k
Amira Klip	16.9k 0.9×	7.5k 0.9×	5.6k 0.7×	5.9k 0.9×	2.3k 0.7×	335	24.5k
Jeffrey E. Pessin	15.1k 0.8×	6.2k 0.7×	5.1k 0.7×	5.1k 0.8×	3.2k 1.1×	305	24.2k
Michael Czech	16.9k 0.9×	8.0k 0.9×	5.1k 0.7×	4.9k 0.8×	4.8k 1.6×	299	28.7k
Robert V. Farese	17.9k 0.9×	8.4k 1.0×	4.5k 0.6×	5.6k 0.9×	5.1k 1.7×	238	34.9k
Morris J. Birnbaum	27.6k 1.4×	9.9k 1.2×	4.0k 0.5×	8.3k 1.3×	5.7k 1.8×	243	41.3k
Bruce E. Kemp	31.0k 1.6×	11.1k 1.3×	4.7k 0.6×	8.7k 1.3×	5.2k 1.7×	451	44.8k
John H. Exton	18.0k 0.9×	5.8k 0.7×	5.7k 0.7×	4.5k 0.7×	1.6k 0.5×	275	27.1k
Alan R. Saltiel	25.3k 1.3×	11.2k 1.3×	6.4k 0.8×	5.8k 0.9×	9.4k 3.1×	280	45.5k
Gary W. Cline	15.2k 0.8×	13.5k 1.6×	3.0k 0.4×	5.3k 0.8×	7.3k 2.4×	215	31.3k
M. Daniel Lane	19.2k 1.0×	11.1k 1.3×	4.6k 0.6×	3.9k 0.6×	7.6k 2.5×	310	33.7k

Countries citing papers authored by David E. James

Since Specialization

Citations

This map shows the geographic impact of David E. James'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 E. James with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David E. James more than expected).

Fields of papers citing papers by David E. James

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David E. James. 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 E. James. The network helps show where David E. James may publish in the future.

Co-authorship network of co-authors of David E. James

This figure shows the co-authorship network connecting the top 25 collaborators of David E. James. A scholar is included among the top collaborators of David E. James 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 E. James. David E. James is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Cooke, Kristen C., Stewart W. C. Masson, Jonathan G. Crowston, et al.. (2025). Cold exposure stimulates cross-tissue metabolic rewiring to fuel glucose-dependent thermogenesis in brown adipose tissue. Science Advances. 11(24). eadt7369–eadt7369.

2.

Humphrey, Sean J., Sheree D. Martin, Christopher S. Shaw, et al.. (2025). Adipose tissue protein kinase D: regulation of signaling networks and its sex-dependent effects on metabolism. American Journal of Physiology-Endocrinology and Metabolism. 329(1). E67–E85.

3.

Masson, Stewart W. C., et al.. (2024). Unlocking metabolic insights with mouse genetic diversity. The EMBO Journal. 43(21). 4814–4821. 2 indexed citations

4.

Cooke, Kristen C., Jacqueline Stöckli, Belinda Yau, et al.. (2024). The metabolic consequences of ‘yo-yo’ dieting are markedly influenced by genetic diversity. International Journal of Obesity. 48(8). 1170–1179. 2 indexed citations

5.

Díaz‐Vegas, Alexis, Søren Madsen, Kristen C. Cooke, et al.. (2023). Mitochondrial electron transport chain, ceramide, and coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle. eLife. 12. 23 indexed citations

6.

Díaz‐Vegas, Alexis, Søren Madsen, Kristen C. Cooke, et al.. (2023). Mitochondrial electron transport chain, ceramide, and coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle. eLife. 12. 17 indexed citations

7.

Allayee, Hooman, Charles R. Farber, Marcus Seldin, et al.. (2023). Systems genetics approaches for understanding complex traits with relevance for human disease. eLife. 12. 11 indexed citations

8.

Molendijk, Jeffrey, Ronnie Blazev, Richard J. Mills, et al.. (2022). Proteome-wide systems genetics identifies UFMylation as a regulator of skeletal muscle function. eLife. 11. 9 indexed citations

9.

Francis, Deanne, Shila Ghazanfar, Essi Havula, et al.. (2021). Genome-wide analysis in Drosophila reveals diet-by-gene interactions and uncovers diet-responsive genes. G3 Genes Genomes Genetics. 11(10). 6 indexed citations

10.

Kim, Tai-Yun, Owen Tang, Stephen T. Vernon, et al.. (2021). A hierarchical approach to removal of unwanted variation for large-scale metabolomics data. Nature Communications. 12(1). 4992–4992. 28 indexed citations

11.

Yau, Belinda, Alexis Díaz‐Vegas, Elise J. Needham, et al.. (2021). Proteomic pathways to metabolic disease and type 2 diabetes in the pancreatic islet. iScience. 24(10). 103099–103099. 11 indexed citations

12.

Li, Mengbo, Benjamin L. Parker, Benjamin Hunter, et al.. (2020). Core functional nodes and sex-specific pathways in human ischaemic and dilated cardiomyopathy. Nature Communications. 11(1). 2843–2843. 57 indexed citations

13.

Needham, Elise J., et al.. (2019). Illuminating the dark phosphoproteome. Science Signaling. 12(565). 212 indexed citations

14.

Oya, Nereida Jiménez de, William P. Esler, Kim Huard, et al.. (2019). Targeting host metabolism by inhibition of acetyl-Coenzyme A carboxylase reduces flavivirus infection in mouse models. Emerging Microbes & Infections. 8(1). 624–636. 36 indexed citations

15.

Norris, Dougall M., Pengyi Yang, James R. Krycer, et al.. (2017). An improved Akt reporter reveals intra- and inter-cellular heterogeneity and oscillations in signal transduction. Journal of Cell Science. 130(16). 2757–2766. 15 indexed citations

16.

Simpson, Stephen J., David G. Le Couteur, David E. James, et al.. (2017). The Geometric Framework for Nutrition as a tool in precision medicine. PubMed. 4(3). 217–226. 65 indexed citations

17.

Christie, Michelle P., Andrew E. Whitten, Gordon J. King, et al.. (2012). Low-resolution solution structures of Munc18:Syntaxin protein complexes indicate an open binding mode driven by the Syntaxin N-peptide. Proceedings of the National Academy of Sciences. 109(25). 9816–9821. 43 indexed citations

18.

James, David E.. (2005). MUNC-ing around with insulin action. Journal of Clinical Investigation. 115(2). 219–221. 25 indexed citations

19.

James, David E.. (2005). MUNC-ing around with insulin action. Journal of Clinical Investigation. 115(2). 219–221. 21 indexed citations

20.

Bryant, Nia J. & David E. James. (2003). The Sec1p/Munc18 (SM) protein, Vps45p, cycles on and off membranes during vesicle transport. The Journal of Cell Biology. 161(4). 691–696. 33 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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