Shama R. Iyer

1.2k total citations
33 papers, 731 citations indexed

About

Shama R. Iyer is a scholar working on Molecular Biology, Surgery and Biomedical Engineering. According to data from OpenAlex, Shama R. Iyer has authored 33 papers receiving a total of 731 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 11 papers in Surgery and 9 papers in Biomedical Engineering. Recurrent topics in Shama R. Iyer's work include Muscle Physiology and Disorders (17 papers), Muscle activation and electromyography studies (6 papers) and Adipose Tissue and Metabolism (4 papers). Shama R. Iyer is often cited by papers focused on Muscle Physiology and Disorders (17 papers), Muscle activation and electromyography studies (6 papers) and Adipose Tissue and Metabolism (4 papers). Shama R. Iyer collaborates with scholars based in United States, India and Germany. Shama R. Iyer's co-authors include Richard M. Lovering, Sameer B. Shah, Joseph P. Stains, Ana P. Valencia, Kathryn R. Wagner, Jordana Gilbert‐Honick, Espen E. Spangenburg, Warren L. Grayson, Hai‐Quan Mao and Su Xu and has published in prestigious journals such as Biomaterials, The FASEB Journal and Journal of Cell Science.

In The Last Decade

Shama R. Iyer

32 papers receiving 728 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shama R. Iyer United States 16 415 236 161 131 103 33 731
Darren J. Player United Kingdom 16 353 0.9× 197 0.8× 314 2.0× 102 0.8× 86 0.8× 37 741
Farshad Babaeijandaghi Canada 9 491 1.2× 260 1.1× 156 1.0× 164 1.3× 164 1.6× 11 864
Dilip Thomas United States 16 284 0.7× 223 0.9× 302 1.9× 42 0.3× 174 1.7× 33 722
Jana Musı́lková Czechia 13 283 0.7× 208 0.9× 172 1.1× 85 0.6× 192 1.9× 37 865
Christopher J. O’Conor United States 12 353 0.9× 254 1.1× 177 1.1× 161 1.2× 112 1.1× 22 1.2k
Yacine Kharraz Spain 8 830 2.0× 292 1.2× 136 0.8× 231 1.8× 50 0.5× 9 1.2k
Song Wu China 17 547 1.3× 222 0.9× 162 1.0× 45 0.3× 49 0.5× 39 1.2k
Ashley G. Goodman United States 8 241 0.6× 116 0.5× 151 0.9× 72 0.5× 56 0.5× 9 704
J.P. Dillon United Kingdom 14 264 0.6× 104 0.4× 132 0.8× 64 0.5× 48 0.5× 26 764
Piera Smeriglio United States 16 384 0.9× 148 0.6× 82 0.5× 43 0.3× 64 0.6× 31 725

Countries citing papers authored by Shama R. Iyer

Since Specialization
Citations

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

Fields of papers citing papers by Shama R. Iyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shama R. Iyer

This figure shows the co-authorship network connecting the top 25 collaborators of Shama R. Iyer. A scholar is included among the top collaborators of Shama R. Iyer 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 Shama R. Iyer. Shama R. Iyer 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.
Sun, Congshan, Suraj Kannan, In Young Choi, et al.. (2022). Human pluripotent stem cell-derived myogenic progenitors undergo maturation to quiescent satellite cells upon engraftment. Cell stem cell. 29(4). 610–619.e5. 17 indexed citations
2.
Moyer, Adam L., Congshan Sun, Ting Liu, et al.. (2021). Mss51 deletion increases endurance and ameliorates histopathology in the mdx mouse model of Duchenne muscular dystrophy. The FASEB Journal. 35(2). e21276–e21276. 9 indexed citations
3.
Iyer, Shama R., Ru‐ching Hsia, Eric S. Folker, & Richard M. Lovering. (2021). Age-dependent changes in nuclear-cytoplasmic signaling in skeletal muscle. Experimental Gerontology. 150. 111338–111338. 15 indexed citations
4.
Iyer, Shama R., Eric S. Folker, & Richard M. Lovering. (2021). The Nucleoskeleton: Crossroad of Mechanotransduction in Skeletal Muscle. Frontiers in Physiology. 12. 724010–724010. 8 indexed citations
5.
Sun, Congshan, In Young Choi, Peter Andersen, et al.. (2020). Duchenne muscular dystrophy hiPSC-derived myoblast drug screen identifies compounds that ameliorate disease in mdx mice. JCI Insight. 5(11). 24 indexed citations
6.
Lovering, Richard M., Shama R. Iyer, Benjamin Edwards, & Kay E. Davies. (2020). Alterations of neuromuscular junctions in Duchenne muscular dystrophy. Neuroscience Letters. 737. 135304–135304. 27 indexed citations
7.
8.
Moyer, Adam L., Congshan Sun, Ting Liu, et al.. (2019). Mss51 deletion enhances muscle metabolism and glucose homeostasis in mice. JCI Insight. 4(20). 18 indexed citations
9.
Michailowsky, Vladimir, Bidyottam Mittra, Shama R. Iyer, et al.. (2019). Defects in sarcolemma repair and skeletal muscle function after injury in a mouse model of Niemann-Pick type A/B disease. Skeletal Muscle. 9(1). 1–1. 18 indexed citations
10.
Gilbert‐Honick, Jordana, Shama R. Iyer, Richard M. Lovering, et al.. (2018). Engineering functional and histological regeneration of vascularized skeletal muscle. Biomaterials. 164. 70–79. 88 indexed citations
11.
Valencia, Ana P., Jim K. Lai, Shama R. Iyer, et al.. (2018). Fatty Infiltration Is a Prognostic Marker of Muscle Function After Rotator Cuff Tear. The American Journal of Sports Medicine. 46(9). 2161–2169. 68 indexed citations
12.
Valencia, Ana P., Shama R. Iyer, Espen E. Spangenburg, Mohit N. Gilotra, & Richard M. Lovering. (2017). Impaired contractile function of the supraspinatus in the acute period following a rotator cuff tear. BMC Musculoskeletal Disorders. 18(1). 436–436. 9 indexed citations
13.
Pratt, Stephen J. P., Shama R. Iyer, Sameer B. Shah, & Richard M. Lovering. (2017). Imaging Analysis of the Neuromuscular Junction in Dystrophic Muscle. Methods in molecular biology. 1687. 57–72. 15 indexed citations
14.
Moorer, Megan C., et al.. (2017). Defective signaling, osteoblastogenesis and bone remodeling in a mouse model of connexin 43 C-terminal truncation. Journal of Cell Science. 130(3). 531–540. 54 indexed citations
15.
Iyer, Shama R., Su Xu, Joseph P. Stains, Craig Bennett, & Richard M. Lovering. (2016). Superparamagnetic Iron Oxide Nanoparticles in Musculoskeletal Biology. Tissue Engineering Part B Reviews. 23(4). 373–385. 28 indexed citations
16.
Iyer, Shama R., et al.. (2016). Novel multi-functional fluid flow device for studying cellular mechanotransduction. Journal of Biomechanics. 49(16). 4173–4179. 15 indexed citations
17.
Iyer, Shama R., Ana P. Valencia, Erick O. Hernández‐Ochoa, & Richard M. Lovering. (2016). In Vivo Assessment of Muscle Contractility in Animal Studies. Methods in molecular biology. 1460. 293–307. 25 indexed citations
18.
Iyer, Shama R., et al.. (2015). BIOMECHANICAL PROPERTIES OF MESHES FOLLOWING IMPLANTATION IN THE RAT ABDOMINAL WALL MODEL. Journal of Mechanics in Medicine and Biology. 16(3). 1650036–1650036. 1 indexed citations
19.
20.
Iyer, Shama R., Helen Valentine, Sean P. McDonough, et al.. (2013). Effects of Chitosan Coatings on Polypropylene Mesh for Implantation in a Rat Abdominal Wall Model. Tissue Engineering Part A. 19(23-24). 2713–2723. 36 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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