May Khanna
Impact in
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- Axon Guidance and Neuronal Signaling
- Neuroscience and Neuropharmacology Research
- Physiology top 5%
- Pain Mechanisms and Treatments
Papers in
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- RNA Research and Splicing 9
- RNA and protein synthesis mechanisms 5
- Ion channel regulation and function 4
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- Axon Guidance and Neuronal Signaling 10
- Neuroscience and Neuropharmacology Research 6
- Neuropeptides and Animal Physiology 4
- Co-authors
- Rajesh Khanna (30 shared papers)Aubin Moutal (20 shared papers)Liberty François‐Moutal (20 shared papers)Samantha Perez‐Miller (16 shared papers)David D. Scott (9 shared papers)Samy O. Meroueh (9 shared papers)Xiaofang Yang (6 shared papers)Erik T. Dustrude (5 shared papers)
- Journals
- Pain (7 papers)Channels (4 papers)Proceedings of the National Academy of Sciences (3 papers)ACS Chemical Biology (3 papers)RNA (2 papers)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
May Khanna
54 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 101
- Cellular and Molecular Neuroscience 512
- Physiology 466
- Molecular Biology 1.2k
- Neurology 228
- Cell Biology 182
Countries citing papers authored by May Khanna
This map shows the geographic impact of May 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 May Khanna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites May Khanna more than expected).
Fields of papers citing papers by May Khanna
This network shows the impact of papers produced by May 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 May Khanna. The network helps show where May Khanna may publish in the future.
Co-authors
The 25 scholars most cited alongside May Khanna, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 150 | |
| 2 | 2014 | 116 | |
| 3 | 2019 | 104 | |
| 4 | 2016 | 100 | |
| 5 | 2003 | 94 | |
| 6 | 2011 | 66 | |
| 7 | 2017 | 65 | |
| 8 | 2015 | 63 | |
| 9 | 2019 | 57 | |
| 10 | 2011 | 51 | |
| 11 | 2018 | 50 | |
| 12 | 2016 | 49 | |
| 13 | 2015 | 47 | |
| 14 | 2012 | 46 | |
| 15 | 2018 | 46 | |
| 16 | 2022 | 43 | |
| 17 | 2011 | 42 | |
| 18 | 2013 | 42 | |
| 19 | 2015 | 41 | |
| 20 | 2012 | 37 |
About May Khanna
May Khanna is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Physiology, Neurology and Cancer Research, having authored 56 papers that have together received 2.0k indexed citations. Recurring topics across this work include Pain Mechanisms and Treatments (11 papers), Axon Guidance and Neuronal Signaling (10 papers), RNA Research and Splicing (9 papers), Amyotrophic Lateral Sclerosis Research (7 papers), Neuroscience and Neuropharmacology Research (6 papers), RNA and protein synthesis mechanisms (5 papers), Ion channel regulation and function (4 papers) and Neuropeptides and Animal Physiology (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (512 citations), Physiology (466 citations), Molecular Biology (1.2k citations), Neurology (228 citations) and Cell Biology (182 citations). May Khanna has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Rajesh Khanna, Aubin Moutal, Liberty François‐Moutal, Samantha Perez‐Miller, David D. Scott, Samy O. Meroueh, Xiaofang Yang, Erik T. Dustrude, Yuying Wang and Stefan Kaskel. Their work appears in journals such as Pain, Channels, Proceedings of the National Academy of Sciences, ACS Chemical Biology and RNA.
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.