Rajesh Khanna

8.6k total citations
223 papers, 6.1k citations indexed

About

Rajesh Khanna is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Rajesh Khanna has authored 223 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 131 papers in Molecular Biology, 128 papers in Cellular and Molecular Neuroscience and 79 papers in Physiology. Recurrent topics in Rajesh Khanna's work include Pain Mechanisms and Treatments (69 papers), Axon Guidance and Neuronal Signaling (65 papers) and Neuroscience and Neuropharmacology Research (60 papers). Rajesh Khanna is often cited by papers focused on Pain Mechanisms and Treatments (69 papers), Axon Guidance and Neuronal Signaling (65 papers) and Neuroscience and Neuropharmacology Research (60 papers). Rajesh Khanna collaborates with scholars based in United States, China and Canada. Rajesh Khanna's co-authors include Aubin Moutal, Lyanne C. Schlichter, Sarah M. Wilson, Joel M. Brittain, May Khanna, Yuying Wang, Fletcher A. White, Leonard K. Kaczmarek, Erik T. Dustrude and Matthew S. Ripsch and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Rajesh Khanna

216 papers receiving 6.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rajesh Khanna United States 45 3.2k 2.7k 1.8k 672 583 223 6.1k
Philippe Marin France 48 3.4k 1.1× 2.8k 1.0× 1.3k 0.7× 559 0.8× 452 0.8× 145 6.2k
Jonathan D. Geiger United States 46 3.1k 1.0× 2.1k 0.8× 2.2k 1.2× 756 1.1× 522 0.9× 163 8.2k
Hermann Lübbert Germany 48 4.0k 1.3× 2.7k 1.0× 753 0.4× 396 0.6× 932 1.6× 104 7.1k
Kimberly A. Moore United States 31 1.6k 0.5× 2.0k 0.7× 3.0k 1.7× 506 0.8× 400 0.7× 49 5.6k
Adele M. Snowman United States 45 4.5k 1.4× 2.1k 0.8× 1.9k 1.0× 1.1k 1.6× 218 0.4× 63 8.3k
Klaus Fink Germany 39 4.0k 1.3× 2.8k 1.0× 982 0.5× 367 0.5× 721 1.2× 82 7.4k
Hoon Ryu United States 48 5.3k 1.7× 2.4k 0.9× 1.8k 1.0× 542 0.8× 1.4k 2.4× 178 9.1k
John E. Pintar United States 59 5.4k 1.7× 4.7k 1.7× 2.0k 1.1× 720 1.1× 408 0.7× 180 10.1k
Ikuo Tooyama Japan 48 2.9k 0.9× 2.2k 0.8× 2.2k 1.2× 406 0.6× 1.4k 2.4× 300 8.0k
Louis B. Hersh United States 55 4.9k 1.5× 4.1k 1.5× 3.3k 1.8× 744 1.1× 565 1.0× 223 10.5k

Countries citing papers authored by Rajesh Khanna

Since Specialization
Citations

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

Fields of papers citing papers by Rajesh Khanna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rajesh Khanna

This figure shows the co-authorship network connecting the top 25 collaborators of Rajesh Khanna. A scholar is included among the top collaborators of Rajesh Khanna 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 Khanna. Rajesh Khanna 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.
Mwirigi, Juliet M., Anna Cervantes, Peter Horton, et al.. (2025). Genetic editing of primary human dorsal root ganglion neurons using CRISPR-Cas9. Scientific Reports. 15(1). 11116–11116.
2.
Allen, Kyle D., et al.. (2024). The contribution of clock genes BMAL1 and PER2 in osteoarthritis-associated pain. PubMed. 17. 100177–100177. 2 indexed citations
3.
Castañeda‐Corral, Gabriela, et al.. (2024). Nociplastic pain mechanisms and toll-like receptors as promising targets for its management. Pain. 165(10). 2150–2164. 5 indexed citations
4.
Allen, Heather N., Aida Calderón‐Rivera, Kimberly Gómez, et al.. (2023). Intranasal CRMP2-Ubc9 inhibitor regulates NaV1.7 to alleviate trigeminal neuropathic pain. Pain. 165(3). 573–588. 13 indexed citations
5.
Tu, Nguyen Huu, María Daniela Santi, Manikandan Vinu, et al.. (2023). The Ca 2+ channel ORAI1 is a regulator of oral cancer growth and nociceptive pain. Science Signaling. 16(801). eadf9535–eadf9535. 5 indexed citations
6.
Stratton, Harrison J., Lisa Boinon, Kimberly Gómez, et al.. (2022). Targeting the vascular endothelial growth factor A/neuropilin 1 axis for relief of neuropathic pain. Pain. 164(7). 1473–1488. 10 indexed citations
7.
Cai, Song, Kimberly Gómez, Aubin Moutal, & Rajesh Khanna. (2021). Targeting T-type/CaV3.2 channels for chronic pain. Translational research. 234. 20–30. 58 indexed citations
8.
Stratton, Harrison J. & Rajesh Khanna. (2020). Sculpting Dendritic Spines during Initiation and Maintenance of Neuropathic Pain. Journal of Neuroscience. 40(40). 7578–7589. 29 indexed citations
9.
Pulliam, Casey, Vickie Knepper-Adrian, Rajesh Khanna, et al.. (2020). RABL6A Is an Essential Driver of MPNSTs that Negatively Regulates the RB1 Pathway and Sensitizes Tumor Cells to CDK4/6 Inhibitors. Clinical Cancer Research. 26(12). 2997–3011. 40 indexed citations
10.
Moutal, Aubin, Song Cai, Jie Yu, et al.. (2020). Studies on CRMP2 SUMOylation–deficient transgenic mice identify sex-specific Nav1.7 regulation in the pathogenesis of chronic neuropathic pain. Pain. 161(11). 2629–2651. 27 indexed citations
11.
Moutal, Aubin, Laurent Martin, Lisa Boinon, et al.. (2020). SARS-CoV-2 spike protein co-opts VEGF-A/neuropilin-1 receptor signaling to induce analgesia. Pain. 162(1). 243–252. 117 indexed citations
12.
Khanna, Rajesh, Jie Yu, Xiaofang Yang, et al.. (2019). Targeting the CaVα–CaVβ interaction yields an antagonist of the N-type CaV2.2 channel with broad antinociceptive efficacy. Pain. 160(7). 1644–1661. 35 indexed citations
13.
Zhou, Yuan, Song Cai, Aubin Moutal, et al.. (2019). The Natural Flavonoid Naringenin Elicits Analgesia through Inhibition of NaV1.8 Voltage-Gated Sodium Channels. ACS Chemical Neuroscience. 10(12). 4834–4846. 28 indexed citations
14.
Moutal, Aubin, Jami L. Saloman, Karen A. Hartnett, et al.. (2017). Targeting a Potassium Channel/Syntaxin Interaction Ameliorates Cell Death in Ischemic Stroke. Journal of Neuroscience. 37(23). 5648–5658. 26 indexed citations
15.
Moutal, Aubin, Xiaofang Yang, Wennan Li, et al.. (2017). CRISPR/Cas9 editing of Nf1 gene identifies CRMP2 as a therapeutic target in neurofibromatosis type 1-related pain that is reversed by (S)-Lacosamide. Pain. 158(12). 2301–2319. 63 indexed citations
16.
Ibrahim, Mohab, Amol Patwardhan, Aubin Moutal, et al.. (2016). Long-lasting antinociceptive effects of green light in acute and chronic pain in rats. Pain. 158(2). 347–360. 82 indexed citations
17.
Moutal, Aubin, Jérôme Honnorat, Chantal Watrin, et al.. (2015). CRMP5 Controls Glioblastoma Cell Proliferation and Survival through Notch-Dependent Signaling. Cancer Research. 75(17). 3519–3528. 37 indexed citations
18.
19.
Wilson, Sarah M. & Rajesh Khanna. (2015). Specific binding of lacosamide to collapsin response mediator protein 2 (CRMP2) and direct impairment of its canonical function: implications for the therapeutic potential of lacosamide. PMC. 1 indexed citations
20.
Brittain, Joel M., Rui Pan, Haitao You, et al.. (2012). Disruption of NMDAR–CRMP-2 signaling protects against focal cerebral ischemic damage in the rat middle cerebral artery occlusion model. Channels. 6(1). 52–59. 30 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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