Nirupa Chaudhari

7.3k total citations · 3 hit papers
69 papers, 5.5k citations indexed

About

Nirupa Chaudhari is a scholar working on Nutrition and Dietetics, Sensory Systems and Biomedical Engineering. According to data from OpenAlex, Nirupa Chaudhari has authored 69 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Nutrition and Dietetics, 44 papers in Sensory Systems and 27 papers in Biomedical Engineering. Recurrent topics in Nirupa Chaudhari's work include Biochemical Analysis and Sensing Techniques (50 papers), Olfactory and Sensory Function Studies (44 papers) and Advanced Chemical Sensor Technologies (27 papers). Nirupa Chaudhari is often cited by papers focused on Biochemical Analysis and Sensing Techniques (50 papers), Olfactory and Sensory Function Studies (44 papers) and Advanced Chemical Sensor Technologies (27 papers). Nirupa Chaudhari collaborates with scholars based in United States, Russia and Germany. Nirupa Chaudhari's co-authors include Stephen D. Roper, Gennady Dvoryanchikov, Elizabeth Pereira, Ana Marie Landin, Yutaka Maruyama, Joung W. Kim, Kurt G. Beam, William E. Hahn, Hui Yang and Seth M. Tomchik and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Nirupa Chaudhari

69 papers receiving 5.4k citations

Hit Papers

The cell biology of taste 2010 2026 2015 2020 2010 2017 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nirupa Chaudhari United States 38 3.9k 3.5k 2.4k 1.4k 826 69 5.5k
Sue C. Kinnamon United States 43 4.8k 1.2× 4.2k 1.2× 2.7k 1.1× 1.2k 0.8× 1.2k 1.5× 96 5.9k
Stephen D. Roper United States 53 6.8k 1.7× 5.8k 1.6× 3.8k 1.6× 2.1k 1.5× 2.0k 2.4× 129 9.0k
Göran Hellekant United States 25 2.1k 0.5× 1.7k 0.5× 989 0.4× 656 0.5× 389 0.5× 60 2.8k
Yuzo Ninomiya Japan 53 8.0k 2.0× 6.5k 1.8× 3.6k 1.5× 1.2k 0.9× 944 1.1× 187 9.4k
Mark A. Hoon United States 32 7.4k 1.9× 6.7k 1.9× 3.9k 1.6× 2.0k 1.4× 2.1k 2.6× 52 10.9k
Jean‐Pierre Montmayeur France 21 1.5k 0.4× 1.2k 0.3× 739 0.3× 790 0.6× 554 0.7× 45 2.7k
Steven D. Munger United States 28 1.9k 0.5× 1.9k 0.5× 729 0.3× 477 0.3× 972 1.2× 52 2.9k
Timothy A. Gilbertson United States 30 2.0k 0.5× 1.6k 0.5× 1.0k 0.4× 665 0.5× 747 0.9× 66 3.2k
Kunio Torii Japan 31 1.7k 0.4× 987 0.3× 619 0.3× 580 0.4× 428 0.5× 142 3.2k
Paul Feinstein United States 30 2.9k 0.7× 3.1k 0.9× 462 0.2× 1.8k 1.3× 3.5k 4.3× 52 6.3k

Countries citing papers authored by Nirupa Chaudhari

Since Specialization
Citations

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

Fields of papers citing papers by Nirupa Chaudhari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nirupa Chaudhari

This figure shows the co-authorship network connecting the top 25 collaborators of Nirupa Chaudhari. A scholar is included among the top collaborators of Nirupa Chaudhari 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 Nirupa Chaudhari. Nirupa Chaudhari 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.
Dvoryanchikov, Gennady, et al.. (2022). Selectively Imaging Cranial Sensory Ganglion Neurons Using AAV-PHP.S. eNeuro. 9(3). ENEURO.0373–21.2022. 6 indexed citations
2.
Chaudhari, Nirupa. (2021). Is there a role for GABA in peripheral taste processing. Current Opinion in Physiology. 20. 105–111. 1 indexed citations
3.
Eshraghi, Adrien A., et al.. (2020). Potential Mechanisms for COVID-19 Induced Anosmia and Dysgeusia. Frontiers in Physiology. 11. 1039–1039. 27 indexed citations
4.
Breza, Joseph M., et al.. (2019). Oral thermosensing by murine trigeminal neurons: modulation by capsaicin, menthol and mustard oil. The Journal of Physiology. 597(7). 2045–2061. 27 indexed citations
5.
Kurtenbach, Sarah, Garrett M. Goss, Stefania Goncalves, et al.. (2019). Cell-Based Therapy Restores Olfactory Function in an Inducible Model of Hyposmia. Stem Cell Reports. 12(6). 1354–1365. 40 indexed citations
6.
Roper, Stephen D., et al.. (2019). The Role of the Anion in Salt (NaCl) Detection by Mouse Taste Buds. Journal of Neuroscience. 39(32). 6224–6232. 64 indexed citations
7.
Izenwasser, Sari, et al.. (2015). Cocaine decreases saccharin preference without altering sweet taste sensitivity. Pharmacology Biochemistry and Behavior. 133. 18–24. 4 indexed citations
8.
Abouyared, Marianne, et al.. (2014). Oxytocin decreases sweet taste sensitivity in mice. Physiology & Behavior. 141. 103–110. 32 indexed citations
9.
Nagai, Takatoshi, et al.. (2013). Functional Cell Types in Taste Buds Have Distinct Longevities. PLoS ONE. 8(1). e53399–e53399. 139 indexed citations
10.
Huang, Yi-Jen, Leslie M. Stone, Elizabeth Pereira, et al.. (2011). Knocking Out P2X Receptors Reduces Transmitter Secretion in Taste Buds. Journal of Neuroscience. 31(38). 13654–13661. 52 indexed citations
11.
Dvoryanchikov, Gennady, Yi-Jen Huang, René Barro-Soria, Nirupa Chaudhari, & Stephen D. Roper. (2011). GABA, Its Receptors, and GABAergic Inhibition in Mouse Taste Buds. Journal of Neuroscience. 31(15). 5782–5791. 53 indexed citations
12.
Dvoryanchikov, Gennady, et al.. (2010). Oxytocin Signaling in Mouse Taste Buds. PLoS ONE. 5(8). e11980–e11980. 46 indexed citations
13.
Roper, Stephen D. & Nirupa Chaudhari. (2009). Processing Umami and Other Tastes in Mammalian Taste Buds. Annals of the New York Academy of Sciences. 1170(1). 60–65. 8 indexed citations
14.
Chaudhari, Nirupa, Elizabeth Pereira, & Stephen D. Roper. (2009). Taste receptors for umami: the case for multiple receptors. American Journal of Clinical Nutrition. 90(3). 738S–742S. 160 indexed citations
15.
Kim, Joung W., Craig D. Roberts, Stephanie Berg, et al.. (2008). Imaging Cyclic AMP Changes in Pancreatic Islets of Transgenic Reporter Mice. PLoS ONE. 3(5). e2127–e2127. 27 indexed citations
16.
Maruyama, Yutaka, et al.. (2007). The role of pannexin 1 hemichannels in ATP release and cell–cell communication in mouse taste buds. Proceedings of the National Academy of Sciences. 104(15). 6436–6441. 430 indexed citations
17.
Dvoryanchikov, Gennady, Seth M. Tomchik, & Nirupa Chaudhari. (2007). Biogenic amine synthesis and uptake in rodent taste buds. The Journal of Comparative Neurology. 505(3). 302–313. 72 indexed citations
18.
Chaudhari, Nirupa. (2005). Multiple Pathways for Signaling Glutamate Taste in Rodents. Chemical Senses. 30(Supplement 1). i29–i30. 6 indexed citations
19.
Richter, Trevor, Gennady Dvoryanchikov, Nirupa Chaudhari, & Stephen D. Roper. (2004). Acid-Sensitive Two-Pore Domain Potassium (K2P) Channels in Mouse Taste Buds. Journal of Neurophysiology. 92(3). 1928–1936. 83 indexed citations
20.
Chaudhari, Nirupa & Kurt G. Beam. (1993). mRNA for Cardiac Calcium Channel Is Expressed during Development of Skeletal Muscle. Developmental Biology. 155(2). 507–515. 59 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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