Rajesh R. Rao

4.4k total citations · 3 hit papers
18 papers, 3.5k citations indexed

About

Rajesh R. Rao is a scholar working on Physiology, Molecular Biology and Immunology. According to data from OpenAlex, Rajesh R. Rao has authored 18 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Physiology, 7 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Rajesh R. Rao's work include Adipose Tissue and Metabolism (9 papers), Muscle Physiology and Disorders (5 papers) and T-cell and B-cell Immunology (5 papers). Rajesh R. Rao is often cited by papers focused on Adipose Tissue and Metabolism (9 papers), Muscle Physiology and Disorders (5 papers) and T-cell and B-cell Immunology (5 papers). Rajesh R. Rao collaborates with scholars based in United States, Sweden and Australia. Rajesh R. Rao's co-authors include Protul Shrikant, Bruce M. Spiegelman, Kunle Odunsi, Qingsheng Li, Katrin J. Svensson, Jonathan Z. Long, James P. White, Jorge L. Ruas, Mark P. Jedrychowski and Steven P. Gygi and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Immunity.

In The Last Decade

Rajesh R. Rao

18 papers receiving 3.5k citations

Hit Papers

Meteorin-like Is a Hormone that Regulates Immune-Adipose ... 2010 2026 2015 2020 2014 2012 2010 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rajesh R. Rao United States 15 1.8k 1.2k 965 906 483 18 3.5k
Hee‐Woong Lim United States 25 1.5k 0.8× 1.4k 1.2× 380 0.4× 983 1.1× 219 0.5× 51 3.1k
J. Daniel Frantz United States 14 1.1k 0.6× 1.4k 1.2× 274 0.3× 889 1.0× 245 0.5× 14 3.3k
Philip L.S.M. Gordts United States 25 1.6k 0.9× 877 0.7× 270 0.3× 887 1.0× 313 0.6× 57 3.5k
Claire Pecqueur France 31 2.0k 1.1× 1.8k 1.4× 355 0.4× 515 0.6× 101 0.2× 63 3.6k
Glenn C. Rowe United States 28 1.1k 0.6× 2.2k 1.8× 191 0.2× 418 0.5× 194 0.4× 53 3.5k
Srikant Rangaraju United States 30 548 0.3× 682 0.6× 429 0.4× 842 0.9× 270 0.6× 93 2.8k
Tobias Wijshake United States 10 2.2k 1.2× 1.9k 1.5× 930 1.0× 482 0.5× 46 0.1× 11 4.0k
Mauricio Berriel Díaz Germany 26 978 0.5× 1.2k 1.0× 157 0.2× 571 0.6× 96 0.2× 45 2.5k
Marta Llovera Spain 31 843 0.5× 1.5k 1.2× 150 0.2× 258 0.3× 315 0.7× 55 2.5k
Herman I. May United States 19 561 0.3× 1.5k 1.2× 245 0.3× 1.0k 1.1× 65 0.1× 23 3.1k

Countries citing papers authored by Rajesh R. Rao

Since Specialization
Citations

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

Fields of papers citing papers by Rajesh R. Rao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rajesh R. Rao. 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 Rajesh R. Rao. The network helps show where Rajesh R. Rao may publish in the future.

Co-authorship network of co-authors of Rajesh R. Rao

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

All Works

18 of 18 papers shown
1.
Baht, Gurpreet S., Akshay Bareja, David E. Lee, et al.. (2020). Meteorin-like facilitates skeletal muscle repair through a Stat3/IGF-1 mechanism. Nature Metabolism. 2(3). 278–289. 127 indexed citations
2.
Baht, Gurpreet S., Akshay Bareja, David E. Lee, et al.. (2020). Author Correction: Meteorin-like facilitates skeletal muscle repair through a Stat3/IGF-1 mechanism. Nature Metabolism. 2(8). 794–794. 2 indexed citations
3.
Long, Jonathan Z., Katrin J. Svensson, Leslie A. Bateman, et al.. (2016). The Secreted Enzyme PM20D1 Regulates Lipidated Amino Acid Uncouplers of Mitochondria. Cell. 166(2). 424–435. 191 indexed citations
4.
Svensson, Katrin J., Jonathan Z. Long, Mark P. Jedrychowski, et al.. (2016). A Secreted Slit2 Fragment Regulates Adipose Tissue Thermogenesis and Metabolic Function. Cell Metabolism. 23(3). 454–466. 121 indexed citations
5.
Irving, Brian A., Ian R. Lanza, Gregory C. Henderson, et al.. (2015). Combined Training Enhances Skeletal Muscle Mitochondrial Oxidative Capacity Independent of Age. The Journal of Clinical Endocrinology & Metabolism. 100(4). 1654–1663. 107 indexed citations
6.
Rao, Rajesh R., Jonathan Z. Long, James P. White, et al.. (2014). Meteorin-like Is a Hormone that Regulates Immune-Adipose Interactions to Increase Beige Fat Thermogenesis. Cell. 157(6). 1279–1291. 737 indexed citations breakdown →
7.
Long, Jonathan Z., Katrin J. Svensson, Linus Tsai, et al.. (2014). A Smooth Muscle-Like Origin for Beige Adipocytes. Cell Metabolism. 19(5). 810–820. 363 indexed citations
8.
Kong, Xingxing, Alexander S. Banks, Tiemin Liu, et al.. (2014). IRF4 Is a Key Thermogenic Transcriptional Partner of PGC-1α. Cell. 158(1). 69–83. 225 indexed citations
9.
White, James P., Christiane D. Wrann, Rajesh R. Rao, et al.. (2014). G protein-coupled receptor 56 regulates mechanical overload-induced muscle hypertrophy. Proceedings of the National Academy of Sciences. 111(44). 15756–15761. 90 indexed citations
10.
White, James P., Jorge L. Ruas, Rajesh R. Rao, et al.. (2013). A novel PGC‐1á isoform induced by resistance training regulates skeletal muscle hypertrophy. The FASEB Journal. 27(S1). 1 indexed citations
11.
Rao, Rajesh R., Qingsheng Li, Melanie Gubbels Bupp, & Protul Shrikant. (2012). Transcription Factor Foxo1 Represses T-bet-Mediated Effector Functions and Promotes Memory CD8+ T Cell Differentiation. Immunity. 36(3). 374–387. 223 indexed citations
12.
Ruas, Jorge L., James P. White, Rajesh R. Rao, et al.. (2012). A PGC-1α Isoform Induced by Resistance Training Regulates Skeletal Muscle Hypertrophy. Cell. 151(6). 1319–1331. 531 indexed citations breakdown →
13.
Li, Qingsheng, Rajesh R. Rao, Peter S. Goedegebuure, et al.. (2012). Regulating Mammalian Target of Rapamycin To Tune Vaccination-Induced CD8+ T Cell Responses for Tumor Immunity. The Journal of Immunology. 188(7). 3080–3087. 75 indexed citations
14.
Li, Qingsheng, Rajesh R. Rao, Koichi Araki, et al.. (2011). A Central Role for mTOR Kinase in Homeostatic Proliferation Induced CD8+ T Cell Memory and Tumor Immunity. Immunity. 34(4). 541–553. 127 indexed citations
15.
Rao, Rajesh R., Qingsheng Li, Kunle Odunsi, & Protul Shrikant. (2010). The mTOR Kinase Determines Effector versus Memory CD8+ T Cell Fate by Regulating the Expression of Transcription Factors T-bet and Eomesodermin. Immunity. 32(1). 67–78. 516 indexed citations breakdown →
16.
Rao, Rajesh R., Qingsheng Li, & Protul Shrikant. (2010). Fine-tuning CD8+T-cell functional responses: mTOR acts as a rheostat for regulating CD8+T-cell proliferation, survival and differentiation?. Cell Cycle. 9(15). 3068–3073. 15 indexed citations
17.
Shrikant, Protul, Rajesh R. Rao, Qingsheng Li, et al.. (2009). Regulating functional cell fates in CD8 T cells. Immunologic Research. 46(1-3). 12–22. 47 indexed citations
18.
Rao, Rajesh R., et al.. (1966). A comparison of serum creatine phosphokinase and serum glutamic oxalacetic transaminase in skeletal muscle necrosis.. PubMed. 30(6). 157–9. 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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