Gustavo A. Nader

9.6k total citations
49 papers, 2.7k citations indexed

About

Gustavo A. Nader is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Gustavo A. Nader has authored 49 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 14 papers in Cell Biology and 12 papers in Physiology. Recurrent topics in Gustavo A. Nader's work include Muscle Physiology and Disorders (28 papers), Muscle metabolism and nutrition (12 papers) and Nutrition and Health in Aging (7 papers). Gustavo A. Nader is often cited by papers focused on Muscle Physiology and Disorders (28 papers), Muscle metabolism and nutrition (12 papers) and Nutrition and Health in Aging (7 papers). Gustavo A. Nader collaborates with scholars based in United States, Sweden and Brazil. Gustavo A. Nader's co-authors include Karyn A. Esser, Eric P. Hoffman, Ferdinand von Walden, Ingrid E. Lundberg, Thomas J. McLoughlin, Laurie Gutmann, Paul M. Gordon, Emidio E. Pistilli, Peter Stenvinkel and Juan Jesús Carrero and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Nature Communications.

In The Last Decade

Gustavo A. Nader

45 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gustavo A. Nader United States 28 1.6k 850 696 485 327 49 2.7k
Anselmo Sigari Moriscot Brazil 32 1.3k 0.8× 725 0.9× 497 0.7× 393 0.8× 217 0.7× 86 2.5k
Ulrika Raue United States 26 1.4k 0.9× 1.2k 1.4× 910 1.3× 735 1.5× 450 1.4× 41 2.6k
Bryon R. McKay Canada 22 1.3k 0.8× 799 0.9× 654 0.9× 555 1.1× 215 0.7× 36 2.0k
Adam P. Sharples United Kingdom 30 1.2k 0.8× 1.1k 1.3× 700 1.0× 358 0.7× 241 0.7× 59 2.3k
Emidio E. Pistilli United States 29 1.5k 0.9× 944 1.1× 388 0.6× 477 1.0× 152 0.5× 58 2.2k
Michael De Lisio Canada 25 845 0.5× 737 0.9× 510 0.7× 470 1.0× 246 0.8× 84 2.0k
F. Haddad United States 27 1.5k 0.9× 738 0.9× 571 0.8× 566 1.2× 413 1.3× 46 2.5k
Takao Sugiura Japan 27 1.1k 0.7× 709 0.8× 494 0.7× 833 1.7× 210 0.6× 75 2.2k
Joshua P. Nederveen Canada 23 1.0k 0.6× 794 0.9× 477 0.7× 380 0.8× 129 0.4× 53 1.7k
Yoshinobu Ohira Japan 27 1.0k 0.7× 881 1.0× 476 0.7× 493 1.0× 188 0.6× 68 2.0k

Countries citing papers authored by Gustavo A. Nader

Since Specialization
Citations

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

Fields of papers citing papers by Gustavo A. Nader

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gustavo A. Nader. 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 Gustavo A. Nader. The network helps show where Gustavo A. Nader may publish in the future.

Co-authorship network of co-authors of Gustavo A. Nader

This figure shows the co-authorship network connecting the top 25 collaborators of Gustavo A. Nader. A scholar is included among the top collaborators of Gustavo A. Nader 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 Gustavo A. Nader. Gustavo A. Nader 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
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Godwin, Joshua S., Jonathan Michel, Andrew T. Ludlow, et al.. (2024). Relative rDNA copy number is not associated with resistance training-induced skeletal muscle hypertrophy and does not affect myotube anabolism in vitro. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 327(3). R338–R348. 2 indexed citations
3.
Hanna, Samir Abdallah, Bruna Salani Mota, Fábio Ynoe de Moraes, et al.. (2024). Intensity-modulated radiation therapy for early-stage breast cancer: a systematic review and meta-analysis. Sao Paulo Medical Journal. 143(1). e2023324–e2023324. 1 indexed citations
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Roberts, Michael D., John J. McCarthy, Troy A. Hornberger, et al.. (2023). Mechanisms of mechanical overload-induced skeletal muscle hypertrophy: current understanding and future directions. Physiological Reviews. 103(4). 2679–2757. 92 indexed citations
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Guo, Bin, et al.. (2019). Regulation of Ribosome Biogenesis During Skeletal Muscle Hypertrophy. Exercise and Sport Sciences Reviews. 47(2). 91–97. 20 indexed citations
8.
Walden, Ferdinand von, et al.. (2017). Proteasome activity is required for ribosomal DNA transcription and muscle hypertrophy. The FASEB Journal. 31(S1). 1 indexed citations
9.
Barreiro, Esther, Jacob I. Sznajder, Gustavo A. Nader, & G. R. Scott Budinger. (2015). Muscle Dysfunction in Patients with Lung Diseases. A Growing Epidemic. American Journal of Respiratory and Critical Care Medicine. 191(6). 616–619. 31 indexed citations
10.
Stenvinkel, Peter, Juan Jesús Carrero, Ferdinand von Walden, T. Alp İkizler, & Gustavo A. Nader. (2015). Muscle wasting in end-stage renal disease promulgates premature death: established, emerging and potential novel treatment strategies. Nephrology Dialysis Transplantation. 31(7). 1070–1077. 149 indexed citations
11.
Wang, Heng, et al.. (2015). Turning terminally differentiated skeletal muscle cells into regenerative progenitors. Nature Communications. 6(1). 7916–7916. 42 indexed citations
12.
Zong, Mei, Ingela Loell, Eva Lindroos, et al.. (2012). Effects of immunosuppressive treatment on interleukin-15 and interleukin-15 receptor α expression in muscle tissue of patients with polymyositis or dermatomyositis. Annals of the Rheumatic Diseases. 71(6). 1055–1063. 25 indexed citations
13.
Liu, Dongmei, Maureen A. Sartor, Gustavo A. Nader, et al.. (2010). Skeletal muscle gene expression in response to resistance exercise: sex specific regulation. BMC Genomics. 11(1). 659–659. 94 indexed citations
14.
Nader, Gustavo A., Maryam Dastmalchi, Helene Alexanderson, et al.. (2010). A Longitudinal, Integrated, Clinical, Histological and mRNA Profiling Study of Resistance Exercise in Myositis. Molecular Medicine. 16(11-12). 455–464. 74 indexed citations
15.
Lundberg, Ingrid E. & Gustavo A. Nader. (2008). Molecular effects of exercise in patients with inflammatory rheumatic disease. Nature Clinical Practice Rheumatology. 4(11). 597–604. 46 indexed citations
16.
Nader, Gustavo A.. (2006). Concurrent Strength and Endurance Training. Medicine & Science in Sports & Exercise. 38(11). 1965–1970. 184 indexed citations
17.
Kozlov, Serguei, Lídia Hernandez, Po Zhao, et al.. (2006). Loss of emerin at the nuclear envelope disrupts the Rb1/E2F and MyoD pathways during muscle regeneration. Human Molecular Genetics. 15(4). 637–651. 182 indexed citations
18.
Baar, Keith, Gustavo A. Nader, & Sue C. Bodine. (2006). Resistance exercise, muscle loading/unloading and the control of muscle mass. Essays in Biochemistry. 42. 61–74. 77 indexed citations
19.
Nader, Gustavo A., Thomas J. McLoughlin, & Karyn A. Esser. (2005). mTOR function in skeletal muscle hypertrophy: increased ribosomal RNA via cell cycle regulators. American Journal of Physiology-Cell Physiology. 289(6). C1457–C1465. 125 indexed citations
20.
Chen, Yiwen, Gustavo A. Nader, Keith Baar, et al.. (2002). Response of rat muscle to acute resistance exercise defined by transcriptional and translational profiling. The Journal of Physiology. 545(1). 27–41. 132 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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