Padma Nair

21 total papers · 434 total citations
17 papers, 371 citations indexed

About

Padma Nair is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Organic Chemistry. According to data from OpenAlex, Padma Nair has authored 17 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Cellular and Molecular Neuroscience, 10 papers in Molecular Biology and 4 papers in Organic Chemistry. Recurrent topics in Padma Nair's work include Neuropeptides and Animal Physiology (12 papers), Receptor Mechanisms and Signaling (9 papers) and Chemical Synthesis and Analysis (7 papers). Padma Nair is often cited by papers focused on Neuropeptides and Animal Physiology (12 papers), Receptor Mechanisms and Signaling (9 papers) and Chemical Synthesis and Analysis (7 papers). Padma Nair collaborates with scholars based in United States and India. Padma Nair's co-authors include Takashi Yamamoto, Peg Davis, Victor J. Hruby, Frank Porreca, Josephine Lai, Shou-wu Ma, Henry I. Yamamura, Todd W. Vanderah, Edita Navratilova and Nigam P. Rath and has published in prestigious journals such as Journal of Medicinal Chemistry, British Journal of Pharmacology and Tetrahedron Letters.

In The Last Decade

Padma Nair

16 papers receiving 360 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Padma Nair 254 253 100 62 29 17 371
Elżbieta Ber 195 0.8× 284 1.1× 49 0.5× 82 1.3× 18 0.6× 10 424
Karen L. Lobb 169 0.7× 210 0.8× 84 0.8× 70 1.1× 26 0.9× 11 352
David K.H. Lee 155 0.6× 176 0.7× 116 1.2× 173 2.8× 38 1.3× 19 438
Simon N. Owen 262 1.0× 265 1.0× 60 0.6× 89 1.4× 10 0.3× 11 419
Vincent M. Villar 131 0.5× 169 0.7× 102 1.0× 26 0.4× 12 0.4× 29 424
Hardy Sundaram 219 0.9× 266 1.1× 52 0.5× 66 1.1× 24 0.8× 20 412
Rebecca P. Martinez 245 1.0× 242 1.0× 172 1.7× 62 1.0× 14 0.5× 22 427
Kenner C. Rice 267 1.1× 245 1.0× 50 0.5× 40 0.6× 8 0.3× 10 337
Mario Grugni 169 0.7× 207 0.8× 68 0.7× 143 2.3× 35 1.2× 14 423
Jean Morrone 168 0.7× 191 0.8× 26 0.3× 138 2.2× 17 0.6× 9 363

Countries citing papers authored by Padma Nair

Since Specialization
Citations

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

Fields of papers citing papers by Padma Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Padma Nair

This figure shows the co-authorship network connecting the top 25 collaborators of Padma Nair. A scholar is included among the top collaborators of Padma Nair 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 Padma Nair. Padma Nair is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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