Mayank Verma

1.3k total citations
30 papers, 953 citations indexed

About

Mayank Verma is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Mayank Verma has authored 30 papers receiving a total of 953 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 7 papers in Genetics and 6 papers in Surgery. Recurrent topics in Mayank Verma's work include Muscle Physiology and Disorders (22 papers), Tissue Engineering and Regenerative Medicine (6 papers) and Mesenchymal stem cell research (5 papers). Mayank Verma is often cited by papers focused on Muscle Physiology and Disorders (22 papers), Tissue Engineering and Regenerative Medicine (6 papers) and Mesenchymal stem cell research (5 papers). Mayank Verma collaborates with scholars based in United States, Japan and Canada. Mayank Verma's co-authors include Atsushi Asakura, Yoko Asakura, Hiroyuki Hirai, Linda K. McLoon, Shuichi Watanabe, Claire Latroche, Thomas Pengo, Bénédicte Chazaud, Dawn A. Lowe and Jarrod A. Call and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Circulation and Journal of Clinical Investigation.

In The Last Decade

Mayank Verma

29 papers receiving 946 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mayank Verma United States 15 830 237 185 177 104 30 953
Osvaldo Contreras Chile 15 713 0.9× 169 0.7× 199 1.1× 247 1.4× 47 0.5× 25 1.0k
Simona Zanotti Italy 19 774 0.9× 130 0.5× 102 0.6× 113 0.6× 79 0.8× 52 979
Akshay Bareja United States 13 490 0.6× 203 0.9× 218 1.2× 133 0.8× 61 0.6× 21 798
Yefei Wen United States 12 870 1.0× 187 0.8× 257 1.4× 170 1.0× 34 0.3× 16 1.0k
Roseline Yao France 5 723 0.9× 231 1.0× 179 1.0× 195 1.1× 60 0.6× 5 849
Sajedah M. Hindi United States 19 886 1.1× 147 0.6× 285 1.5× 116 0.7× 78 0.8× 24 1.1k
Robert W. Arpke United States 14 896 1.1× 353 1.5× 285 1.5× 141 0.8× 107 1.0× 18 1.1k
Lorenzo Giordani France 18 1.4k 1.7× 288 1.2× 347 1.9× 304 1.7× 78 0.8× 26 1.6k
Michael N. Wosczyna United States 9 844 1.0× 327 1.4× 238 1.3× 328 1.9× 60 0.6× 12 1.3k
Sole Gatto United States 12 859 1.0× 133 0.6× 232 1.3× 195 1.1× 37 0.4× 20 1.1k

Countries citing papers authored by Mayank Verma

Since Specialization
Citations

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

Fields of papers citing papers by Mayank Verma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mayank Verma

This figure shows the co-authorship network connecting the top 25 collaborators of Mayank Verma. A scholar is included among the top collaborators of Mayank Verma 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 Mayank Verma. Mayank Verma 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.
Fogel, Brent L., Thomas Klopstock, David R. Lynch, et al.. (2025). Autosomal Recessive Cerebellar Ataxias: Translating Genes to Therapies. Annals of Neurology. 98(3). 448–470. 1 indexed citations
2.
Asakura, Yoko, et al.. (2025). Protocol for the three-dimensional analysis of rodent skeletal muscle. STAR Protocols. 6(1). 103549–103549. 1 indexed citations
3.
Mitra, Sharmistha, Baozhi Chen, John M. Shelton, et al.. (2024). Myofiber-type-dependent ‘boulder’ or ‘multitudinous pebble’ formations across distinct amylopectinoses. Acta Neuropathologica. 147(1). 46–46. 3 indexed citations
4.
5.
Asakura, Yoko, et al.. (2023). Tissue Clearing and Confocal Microscopic Imaging for Skeletal Muscle. Methods in molecular biology. 2640. 453–462. 3 indexed citations
6.
Kim, Kyutae, et al.. (2023). Three-Dimensional Imaging Analysis for Skeletal Muscle. Methods in molecular biology. 2640. 463–477. 3 indexed citations
7.
Kasiri, Sahba, Mayank Verma, Jun Wu, et al.. (2023). CSTB gene replacement improves neuroinflammation, neurodegeneration and ataxia in murine type 1 progressive myoclonus epilepsy. Gene Therapy. 31(5-6). 234–241. 1 indexed citations
8.
Verma, Mayank, Nan Liu, Brian K. Miller, et al.. (2021). VEGFR-1/Flt-1 inhibition increases angiogenesis and improves muscle function in a mouse model of Duchenne muscular dystrophy. Molecular Therapy — Methods & Clinical Development. 21. 369–381. 12 indexed citations
9.
Bosnakovski, Darko, Ce Yuan, Meiricris Tomaz da Silva, et al.. (2020). Transcriptional and cytopathological hallmarks of FSHD in chronic DUX4-expressing mice. Journal of Clinical Investigation. 130(5). 2465–2477. 47 indexed citations
10.
Verma, Mayank, Yuko Shimizu‐Motohashi, Yoko Asakura, et al.. (2019). Inhibition of FLT1 ameliorates muscular dystrophy phenotype by increased vasculature in a mouse model of Duchenne muscular dystrophy. PLoS Genetics. 15(12). e1008468–e1008468. 21 indexed citations
11.
12.
Verma, Mayank, Yoko Asakura, Thomas Pengo, et al.. (2018). Muscle Satellite Cell Cross-Talk with a Vascular Niche Maintains Quiescence via VEGF and Notch Signaling. Cell stem cell. 23(4). 530–543.e9. 226 indexed citations
13.
Verma, Mayank, et al.. (2017). Extraocular Muscle Repair and Regeneration. Current Ophthalmology Reports. 5(3). 207–215. 29 indexed citations
14.
Verma, Mayank, et al.. (2016). Skeletal Muscle Tissue Clearing for LacZ and Fluorescent Reporters, and Immunofluorescence Staining. Methods in molecular biology. 1460. 129–140. 14 indexed citations
15.
Shi, Hao, Mayank Verma, Lei Zhang, et al.. (2013). Improved regenerative myogenesis and muscular dystrophy in mice lacking Mkp5. Journal of Clinical Investigation. 123(5). 2064–2077. 48 indexed citations
16.
Verma, Mayank, et al.. (2013). Vascular-targeted therapies for Duchenne muscular dystrophy. Skeletal Muscle. 3(1). 9–9. 40 indexed citations
17.
Call, Jarrod A., Gordon L. Warren, Mayank Verma, & Dawn A. Lowe. (2013). Acute failure of action potential conduction in mdx muscle reveals new mechanism of contraction‐induced force loss. The Journal of Physiology. 591(15). 3765–3776. 37 indexed citations
18.
Watanabe, Shuichi, Hiroyuki Hirai, Yoko Asakura, et al.. (2011). MyoD Gene Suppression by Oct4 Is Required for Reprogramming in Myoblasts to Produce Induced Pluripotent Stem Cells. Stem Cells. 29(3). 505–516. 39 indexed citations
19.
Verma, Mayank, Yoko Asakura, Hiroyuki Hirai, et al.. (2010). Flt-1 haploinsufficiency ameliorates muscular dystrophy phenotype by developmentally increased vasculature in mdx mice. Human Molecular Genetics. 19(21). 4145–4159. 48 indexed citations
20.
Asakura, Atsushi, Hiroyuki Hirai, Boris Kablar, et al.. (2007). Increased survival of muscle stem cells lacking the MyoD gene after transplantation into regenerating skeletal muscle. Proceedings of the National Academy of Sciences. 104(42). 16552–16557. 98 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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