Joan Gannon

937 total citations
20 papers, 762 citations indexed

About

Joan Gannon is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Joan Gannon has authored 20 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Cell Biology and 5 papers in Physiology. Recurrent topics in Joan Gannon's work include Muscle Physiology and Disorders (7 papers), Muscle metabolism and nutrition (7 papers) and Nutrition and Health in Aging (3 papers). Joan Gannon is often cited by papers focused on Muscle Physiology and Disorders (7 papers), Muscle metabolism and nutrition (7 papers) and Nutrition and Health in Aging (3 papers). Joan Gannon collaborates with scholars based in Ireland, United States and United Kingdom. Joan Gannon's co-authors include Kay Ohlendieck, Philip Doran, Kathleen O’Connell, Pamela Donoghue, Lisa Staunton, Christopher J. Schofield, John Walsby-Tickle, Syed M. Mohiuddin, Daniel E. Hilleman and Suzana Markolovic and has published in prestigious journals such as Nature Communications, PLoS ONE and American Heart Journal.

In The Last Decade

Joan Gannon

19 papers receiving 753 citations

Peers

Joan Gannon

PHYSI

SPECT

CCM

Francesca Forner Germany

Rudy Stuppard United States

Zachary R. Crook United States

Jean-Marie Dupret France

Masaya Ikegawa Japan

Ludger J.E. Goeminne Switzerland

Miroslav Vařecha Czechia

Boris Reljić Australia

Gwënaël Pottiez France

Hironori Hanada Japan

Francesca Forner Germany

Joan Gannon

802 ×1.5

158 ×0.5

219 ×1.0

PHYSI

408 ×4.2

SPECT

45 ×0.5

CCM

Citations per year, relative to Joan Gannon Joan Gannon (= 1×) peers Francesca Forner

Countries citing papers authored by Joan Gannon

Since Specialization

Citations

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

Fields of papers citing papers by Joan Gannon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joan Gannon. 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 Joan Gannon. The network helps show where Joan Gannon may publish in the future.

Co-authorship network of co-authors of Joan Gannon

This figure shows the co-authorship network connecting the top 25 collaborators of Joan Gannon. A scholar is included among the top collaborators of Joan Gannon 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 Joan Gannon. Joan Gannon 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

Walsby-Tickle, John, Joan Gannon, Chiara Bardella, et al.. (2020). Anion-exchange chromatography mass spectrometry provides extensive coverage of primary metabolic pathways revealing altered metabolism in IDH1 mutant cells. Communications Biology. 3(1). 247–247. 55 indexed citations

Graham, Alexander, Alessia Candeo, Stanley W. Botchway, et al.. (2019). The development of a high throughput drug-responsive model of white adipose tissue comprising adipogenic 3T3-L1 cells in a 3D matrix. Biofabrication. 12(1). 15018–15018. 13 indexed citations

Livermore, Laurent J., Martin Isabelle, Ian M. Bell, et al.. (2019). Rapid intraoperative molecular genetic classification of gliomas using Raman spectroscopy. Neuro-Oncology Advances. 1(1). vdz008–vdz008. 44 indexed citations

Wilkins, Sarah E., Md. Saiful Islam, Joan Gannon, et al.. (2018). JMJD5 is a human arginyl C-3 hydroxylase. Nature Communications. 9(1). 1180–1180. 39 indexed citations

Gannon, Joan, Julia Fernández-Rodrı́guez, Hussam Alamri, et al.. (2014). ARFGAP1 Is Dynamically Associated with Lipid Droplets in Hepatocytes. PLoS ONE. 9(11). e111309–e111309. 13 indexed citations

Gannon, Joan & Kay Ohlendieck. (2012). Subproteomic analysis of basic proteins in aged skeletal muscle following offgel pre-fractionation. Molecular Medicine Reports. 5(4). 993–1000. 14 indexed citations

Doran, Philip, Pamela Donoghue, Kathleen O’Connell, Joan Gannon, & Kay Ohlendieck. (2009). Proteomics of skeletal muscle aging. PROTEOMICS. 9(4). 989–1003. 68 indexed citations

Gannon, Joan, et al.. (2009). Drastic increase of myosin light chain MLC-2 in senescent skeletal muscle indicates fast-to-slow fibre transition in sarcopenia of old age. European Journal of Cell Biology. 88(11). 685–700. 60 indexed citations

O’Connell, Kathleen, Joan Gannon, Philip Doran, & Kay Ohlendieck. (2008). Reduced expression of sarcalumenin and related Ca2+-regulatory proteins in aged rat skeletal muscle. Experimental Gerontology. 43(10). 958–961. 35 indexed citations

10.

O’Connell, Kathleen, Philip Doran, Joan Gannon, & Kay Ohlendieck. (2008). Lectin-based proteomic profiling of aged skeletal muscle: Decreased pyruvate kinase isozyme M1 exhibits drastically increased levels of N-glycosylation. European Journal of Cell Biology. 87(10). 793–805. 33 indexed citations

11.

Gannon, Joan, Lisa Staunton, Kathleen O’Connell, Philip Doran, & Kay Ohlendieck. (2008). Phosphoproteomic analysis of aged skeletal muscle. International Journal of Molecular Medicine. 22(1). 33–42. 85 indexed citations

12.

Doran, Philip, Joan Gannon, Kathleen O’Connell, & Kay Ohlendieck. (2007). Proteomic profiling of animal models mimicking skeletal muscle disorders. PROTEOMICS - CLINICAL APPLICATIONS. 1(9). 1169–1184. 32 indexed citations

13.

Doran, Philip, Joan Gannon, Kathleen O’Connell, & Kay Ohlendieck. (2007). Aging skeletal muscle shows a drastic increase in the small heat shock proteins αB-crystallin/HspB5 and cvHsp/HspB7. European Journal of Cell Biology. 86(10). 629–640. 77 indexed citations

14.

Doran, Philip, et al.. (2007). Opposite pathobiochemical fate of pyruvate kinase and adenylate kinase in aged rat skeletal muscle as revealed by proteomic DIGE analysis. PROTEOMICS. 8(2). 364–377. 73 indexed citations

15.

O’Connell, Kathleen, Joan Gannon, Philip Doran, & Kay Ohlendieck. (2007). Proteomic profiling reveals a severely perturbed protein expression pattern in aged skeletal muscle. International Journal of Molecular Medicine. 20(2). 145–53. 52 indexed citations

16.

Doran, Philip, Pamela Donoghue, Kathleen O’Connell, Joan Gannon, & Kay Ohlendieck. (2007). Proteomic profiling of pathological and aged skeletal muscle fibres by peptide mass fingerprinting (Review). International Journal of Molecular Medicine. 19(4). 547–64. 30 indexed citations

17.

Mohiuddin, Syed M., et al.. (1992). Adverse reactions during acute and chronic class I antiarrhythmic therapy. Current Therapeutic Research. 51(5). 730–738. 1 indexed citations

18.

Mohiuddin, Syed M., et al.. (1992). Efficacy and safety of early versus late initiation of warfarin during heparin therapy in acute thromboembolism. American Heart Journal. 123(3). 729–732. 30 indexed citations

19.

Hilleman, Daniel E., et al.. (1992). Impact of Chronic Oral H₂‐Antagonist Therapy on Left Ventricular Systolic Function and Exercise Capacity. The Journal of Clinical Pharmacology. 32(11). 1033–1037. 8 indexed citations

20.

Gannon, Joan, et al.. (1991). Nutritional Considerations in the Elderly. American Pharmacy. 31(4). 45–50.

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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