Nolan J. Hoffman

2.1k total citations
34 papers, 1.3k citations indexed

About

Nolan J. Hoffman is a scholar working on Molecular Biology, Physiology and Cell Biology. According to data from OpenAlex, Nolan J. Hoffman has authored 34 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 19 papers in Physiology and 9 papers in Cell Biology. Recurrent topics in Nolan J. Hoffman's work include Adipose Tissue and Metabolism (16 papers), Metabolism, Diabetes, and Cancer (14 papers) and Pancreatic function and diabetes (7 papers). Nolan J. Hoffman is often cited by papers focused on Adipose Tissue and Metabolism (16 papers), Metabolism, Diabetes, and Cancer (14 papers) and Pancreatic function and diabetes (7 papers). Nolan J. Hoffman collaborates with scholars based in Australia, United States and Denmark. Nolan J. Hoffman's co-authors include Jeffrey S. Elmendorf, David E. James, Benjamin L. Parker, Rima Chaudhuri, Jamie Whitfield, Kirk M. Habegger, Jacqueline Stöckli, Sean J. Humphrey, Pengyi Yang and Daniel J. Fazakerley and has published in prestigious journals such as Journal of Biological Chemistry, The EMBO Journal and Cell Metabolism.

In The Last Decade

Nolan J. Hoffman

32 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nolan J. Hoffman Australia 19 866 500 332 199 128 34 1.3k
Natalie Lefort United States 18 759 0.9× 519 1.0× 267 0.8× 92 0.5× 111 0.9× 23 1.1k
Alexandra Chadt Germany 22 909 1.0× 568 1.1× 268 0.8× 402 2.0× 172 1.3× 54 1.5k
Christian Pehmøller Denmark 15 1.1k 1.3× 862 1.7× 308 0.9× 419 2.1× 176 1.4× 19 1.6k
Rajan Sah United States 24 1.3k 1.5× 370 0.7× 124 0.4× 207 1.0× 153 1.2× 49 2.3k
Greg M. Kowalski Australia 23 831 1.0× 797 1.6× 281 0.8× 242 1.2× 416 3.3× 60 1.8k
Sylvie Ducreux France 18 870 1.0× 214 0.4× 258 0.8× 132 0.7× 117 0.9× 33 1.3k
Hervé Dubouchaud France 18 722 0.8× 649 1.3× 358 1.1× 79 0.4× 151 1.2× 46 1.6k
Franz P.W. Radner Austria 23 669 0.8× 570 1.1× 378 1.1× 280 1.4× 140 1.1× 35 1.6k
Eili Tranheim Kase Norway 22 661 0.8× 581 1.2× 259 0.8× 239 1.2× 126 1.0× 51 1.3k
Jill M. Schimke United States 13 633 0.7× 769 1.5× 257 0.8× 100 0.5× 141 1.1× 28 1.4k

Countries citing papers authored by Nolan J. Hoffman

Since Specialization
Citations

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

Fields of papers citing papers by Nolan J. Hoffman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nolan J. Hoffman. 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 Nolan J. Hoffman. The network helps show where Nolan J. Hoffman may publish in the future.

Co-authorship network of co-authors of Nolan J. Hoffman

This figure shows the co-authorship network connecting the top 25 collaborators of Nolan J. Hoffman. A scholar is included among the top collaborators of Nolan J. Hoffman 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 Nolan J. Hoffman. Nolan J. Hoffman 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.
Hawley, John A. & Nolan J. Hoffman. (2025). Twenty years of progress in human exercise metabolism research. Nature Reviews Endocrinology. 21(11). 658–659. 1 indexed citations
3.
Bishop, David J., et al.. (2023). Discordant skeletal muscle gene and protein responses to exercise. Trends in Biochemical Sciences. 48(11). 927–936. 14 indexed citations
4.
Lawler, Nathan G., et al.. (2022). Metabolomics reveals mouse plasma metabolite responses to acute exercise and effects of disrupting AMPK-glycogen interactions. Frontiers in Molecular Biosciences. 9. 957549–957549. 4 indexed citations
5.
Lawler, Nathan G., et al.. (2021). Metabolomics and Lipidomics: Expanding the Molecular Landscape of Exercise Biology. Australasian Journal of Paramedicine. 11(3). 151–151. 77 indexed citations
6.
Kim, Hani Jieun, Tai-Yun Kim, Nolan J. Hoffman, et al.. (2021). PhosR enables processing and functional analysis of phosphoproteomic data. Cell Reports. 34(8). 108771–108771. 61 indexed citations
7.
Hoffman, Nolan J., Jamie Whitfield, Sandra Galić, et al.. (2020). Genetic loss of AMPK-glycogen binding destabilises AMPK and disrupts metabolism. Molecular Metabolism. 41. 101048–101048. 32 indexed citations
8.
Whitfield, Jamie, et al.. (2020). Omega-3 Polyunsaturated Fatty Acids Mitigate Palmitate-Induced Impairments in Skeletal Muscle Cell Viability and Differentiation. Frontiers in Physiology. 11. 563–563. 18 indexed citations
9.
Hoffman, Nolan J.. (2017). Omics and Exercise: Global Approaches for Mapping Exercise Biological Networks. Cold Spring Harbor Perspectives in Medicine. 7(10). a029884–a029884. 51 indexed citations
10.
Lee, Robert S., Nolan J. Hoffman, Kate T. Murphy, et al.. (2016). Glucose-6-phosphate dehydrogenase contributes to the regulation of glucose uptake in skeletal muscle. Molecular Metabolism. 5(11). 1083–1091. 15 indexed citations
11.
Kleinert, Maximilian, Benjamin L. Parker, Rima Chaudhuri, et al.. (2016). mTORC2 and AMPK differentially regulate muscle triglyceride content via Perilipin 3. Molecular Metabolism. 5(8). 646–655. 49 indexed citations
12.
Hoffman, Nolan J., Benjamin L. Parker, Rima Chaudhuri, et al.. (2015). Global Phosphoproteomic Analysis of Human Skeletal Muscle Reveals a Network of Exercise-Regulated Kinases and AMPK Substrates. Cell Metabolism. 22(5). 922–935. 320 indexed citations
13.
Hoffman, Nolan J., Benjamin L. Parker, Rima Chaudhuri, et al.. (2015). Global Phosphoproteomic Analysis of Human Skeletal Muscle Reveals a Network of Exercise-Regulated Kinases and AMPK Substrates. Cell Metabolism. 22(5). 948–948. 8 indexed citations
14.
Chaudhuri, Rima, Nolan J. Hoffman, Benjamin L. Parker, et al.. (2015). PhosphOrtholog: a web-based tool for cross-species mapping of orthologous protein post-translational modifications. BMC Genomics. 16(1). 617–617. 23 indexed citations
15.
McCloy, Rachael A., Benjamin L. Parker, Samuel Rogers, et al.. (2015). Global Phosphoproteomic Mapping of Early Mitotic Exit in Human Cells Identifies Novel Substrate Dephosphorylation Motifs. Molecular & Cellular Proteomics. 14(8). 2194–2212. 58 indexed citations
16.
Hoffman, Nolan J., et al.. (2014). Chromium Enhances Insulin Responsiveness via AMPK. Research Bank (Australian Catholic University). 1 indexed citations
17.
Hoffman, Nolan J., et al.. (2014). Chromium enhances insulin responsiveness via AMPK. The Journal of Nutritional Biochemistry. 25(5). 565–572. 49 indexed citations
18.
Parker, Benjamin L., Nicholas E. Shepherd, Sophie Trefely, et al.. (2014). Structural Basis for Phosphorylation and Lysine Acetylation Cross-talk in a Kinase Motif Associated with Myocardial Ischemia and Cardioprotection. Journal of Biological Chemistry. 289(37). 25890–25906. 40 indexed citations
19.
20.
Hoffman, Nolan J. & Jeffrey S. Elmendorf. (2011). Signaling, cytoskeletal and membrane mechanisms regulating GLUT4 exocytosis. Trends in Endocrinology and Metabolism. 22(3). 110–116. 47 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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