James G. Tidball

16.1k total citations · 3 hit papers
136 papers, 12.7k citations indexed

About

James G. Tidball is a scholar working on Molecular Biology, Rehabilitation and Cell Biology. According to data from OpenAlex, James G. Tidball has authored 136 papers receiving a total of 12.7k indexed citations (citations by other indexed papers that have themselves been cited), including 109 papers in Molecular Biology, 37 papers in Rehabilitation and 34 papers in Cell Biology. Recurrent topics in James G. Tidball's work include Muscle Physiology and Disorders (98 papers), Exercise and Physiological Responses (37 papers) and Adipose Tissue and Metabolism (19 papers). James G. Tidball is often cited by papers focused on Muscle Physiology and Disorders (98 papers), Exercise and Physiological Responses (37 papers) and Adipose Tissue and Metabolism (19 papers). James G. Tidball collaborates with scholars based in United States, Russia and Japan. James G. Tidball's co-authors include Melissa J. Spencer, Michelle Wehling‐Henricks, S. Armando Villalta, M. Wehling, Bo Deng, Hal X. Nguyen, Ying Wang, Barbara A. St. Pierre, Jérôme Frenette and Kenneth Dorshkind and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

James G. Tidball

136 papers receiving 12.5k citations

Hit Papers

Inflammatory processes in... 2005 2026 2012 2019 2005 2010 2017 250 500 750 1000

Author Peers

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

Author Last Decade Papers Cites
James G. Tidball 8.6k 3.6k 3.1k 2.1k 1.8k 136 12.7k
Miranda D. Grounds 7.9k 0.9× 1.6k 0.4× 2.7k 0.9× 1.5k 0.7× 2.3k 1.2× 233 10.5k
Sue C. Bodine 9.3k 1.1× 2.0k 0.6× 4.2k 1.4× 3.4k 1.7× 871 0.5× 125 13.1k
Gillian Butler‐Browne 11.0k 1.3× 906 0.2× 3.7k 1.2× 2.8k 1.3× 2.3k 1.2× 292 15.7k
Pura Muñoz‐Cánoves 7.1k 0.8× 1.3k 0.4× 2.9k 0.9× 1.1k 0.5× 1.4k 0.7× 123 10.4k
Shin’ichi Takeda 12.6k 1.5× 1.1k 0.3× 2.9k 0.9× 1.7k 0.8× 3.4k 1.9× 427 17.5k
Antonio L. Serrano 5.5k 0.6× 1.3k 0.3× 2.5k 0.8× 1.2k 0.6× 1.0k 0.6× 67 8.1k
John A. Faulkner 7.6k 0.9× 3.1k 0.8× 3.3k 1.1× 1.8k 0.9× 1.9k 1.0× 226 14.0k
Hannu Kalimo 5.5k 0.6× 599 0.2× 2.4k 0.8× 1.5k 0.7× 2.1k 1.1× 312 15.4k
Se‐Jin Lee 12.2k 1.4× 834 0.2× 4.8k 1.5× 2.9k 1.4× 1.4k 0.8× 96 15.8k
Paolo Bonaldo 6.6k 0.8× 630 0.2× 2.0k 0.6× 2.3k 1.1× 1.6k 0.9× 165 12.3k

Countries citing papers authored by James G. Tidball

Since Specialization
Citations

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

Fields of papers citing papers by James G. Tidball

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James G. Tidball

This figure shows the co-authorship network connecting the top 25 collaborators of James G. Tidball. A scholar is included among the top collaborators of James G. Tidball 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 James G. Tidball. James G. Tidball 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.
Welc, Steven S., Michelle Wehling‐Henricks, Julian N. Ramos, et al.. (2019). Targeting a therapeutic LIF transgene to muscle via the immune system ameliorates muscular dystrophy. Nature Communications. 10(1). 2788–2788. 17 indexed citations
2.
Tidball, James G., Steven S. Welc, & Michelle Wehling‐Henricks. (2018). Immunobiology of Inherited Muscular Dystrophies. Comprehensive physiology. 8(4). 1313–1356. 6 indexed citations
4.
Tidball, James G.. (2011). Mechanisms of Muscle Injury, Repair, and Regeneration. Comprehensive physiology. 1(4). 2029–2062. 14 indexed citations
5.
Sakellariou, Giorgos K., Deborah Pye, Aphrodite Vasilaki, et al.. (2011). Role of superoxide–nitric oxide interactions in the accelerated age‐related loss of muscle mass in mice lacking Cu,Zn superoxide dismutase. Aging Cell. 10(5). 749–760. 64 indexed citations
6.
Tidball, James G.. (2011). Mechanisms of Muscle Injury, Repair, and Regeneration. Comprehensive physiology. 1(4). 2029–2062. 305 indexed citations
7.
Villalta, S. Armando, et al.. (2010). Interleukin-10 reduces the pathology of mdx muscular dystrophy by deactivating M1 macrophages and modulating macrophage phenotype. Human Molecular Genetics. 20(4). 790–805. 235 indexed citations
8.
Wehling‐Henricks, Michelle, Maria C. Jordan, Tomomi Gotoh, et al.. (2010). Arginine Metabolism by Macrophages Promotes Cardiac and Muscle Fibrosis in mdx Muscular Dystrophy. PLoS ONE. 5(5). e10763–e10763. 102 indexed citations
10.
Acharyya, Swarnali, S. Armando Villalta, Nadine Bakkar, et al.. (2007). Interplay of IKK/NF-κB signaling in macrophages and myofibers promotes muscle degeneration in Duchenne muscular dystrophy. Journal of Clinical Investigation. 117(4). 889–901. 366 indexed citations
11.
Spencer, Melissa J. & James G. Tidball. (2001). Do immune cells promote the pathology of dystrophin-deficient myopathies?. Neuromuscular Disorders. 11(6-7). 556–564. 141 indexed citations
12.
Frenette, Jérôme, et al.. (2000). Complement Activation Promotes Muscle Inflammation during Modified Muscle Use. American Journal Of Pathology. 156(6). 2103–2110. 90 indexed citations
13.
Spencer, Melissa J., et al.. (2000). Eosinophilia of Dystrophin-Deficient Muscle Is Promoted by Perforin-Mediated Cytotoxicity by T Cell Effectors. American Journal Of Pathology. 156(5). 1789–1796. 82 indexed citations
14.
Hadhazy, Michele, et al.. (2000). Dominant negative myostatin produces hypertrophy without hyperplasia in muscle. FEBS Letters. 474(1). 71–75. 182 indexed citations
15.
Tidball, James G., Melissa J. Spencer, M. Wehling, & Éliane Lavergne. (1999). Nitric-oxide Synthase Is a Mechanical Signal Transducer That Modulates Talin and Vinculin Expression. Journal of Biological Chemistry. 274(46). 33155–33160. 49 indexed citations
16.
Spencer, Melissa J., Craig M. Walsh, Kenneth Dorshkind, Eva Rodríguez, & James G. Tidball. (1997). Myonuclear apoptosis in dystrophic mdx muscle occurs by perforin-mediated cytotoxicity.. Journal of Clinical Investigation. 99(11). 2745–2751. 143 indexed citations
17.
Spencer, Melissa J., Brandon Lu, & James G. Tidball. (1997). Calpain II expression is increased by changes in mechanical loading of muscle in vivo. Journal of Cellular Biochemistry. 64(1). 55–66. 27 indexed citations
18.
Tidball, James G.. (1995). Inflammatory cell response to acute muscle injury. Medicine & Science in Sports & Exercise. 27(7). 1022–1032. 370 indexed citations
19.
Tidball, James G., et al.. (1992). Developmental modulation of embryonic cardiac myocyte adhesion to cardiac collagens in vitro. Experimental Cell Research. 199(2). 341–348. 4 indexed citations
20.
Law, Douglas J. & James G. Tidball. (1992). Identification of a putative collagen-binding protein from chicken skeletal muscle as glycogen phosphorylase. Biochimica et Biophysica Acta (BBA) - Protein Structure and Molecular Enzymology. 1122(3). 225–233. 2 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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