S.S. Mokha

1.2k total citations
37 papers, 1.0k citations indexed

About

S.S. Mokha is a scholar working on Physiology, Cellular and Molecular Neuroscience and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, S.S. Mokha has authored 37 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Physiology, 30 papers in Cellular and Molecular Neuroscience and 9 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in S.S. Mokha's work include Pain Mechanisms and Treatments (35 papers), Neuropeptides and Animal Physiology (25 papers) and Hormonal and reproductive studies (9 papers). S.S. Mokha is often cited by papers focused on Pain Mechanisms and Treatments (35 papers), Neuropeptides and Animal Physiology (25 papers) and Hormonal and reproductive studies (9 papers). S.S. Mokha collaborates with scholars based in United States, United Kingdom and South Korea. S.S. Mokha's co-authors include Subodh Nag, A. Iggo, Sandra L. Petersen, Paul J. Shughrue, R. F. Hellon, Analisa D. Thompson, Rasneer Sonia Bains, Kaiming Zhang, Kersten M. Small and Richard Fox and has published in prestigious journals such as Journal of Neuroscience, Journal of Neurophysiology and Brain Research.

In The Last Decade

S.S. Mokha

37 papers receiving 999 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S.S. Mokha United States 21 704 582 239 121 106 37 1.0k
Valérie Kayser France 26 1.4k 2.0× 958 1.6× 399 1.7× 191 1.6× 44 0.4× 47 1.8k
P.J. Hope United Kingdom 15 945 1.3× 914 1.6× 389 1.6× 92 0.8× 36 0.3× 25 1.2k
Bernard Calvino France 17 640 0.9× 380 0.7× 156 0.7× 155 1.3× 22 0.2× 46 983
K.R. Gogas United States 14 565 0.8× 467 0.8× 262 1.1× 91 0.8× 19 0.2× 19 924
Heinz-Dieter Hartung Germany 8 378 0.5× 538 0.9× 110 0.5× 62 0.5× 50 0.5× 9 857
Alla Khodorova United States 16 744 1.1× 730 1.3× 502 2.1× 372 3.1× 31 0.3× 31 1.5k
Paul J. Austin Australia 17 1000 1.4× 548 0.9× 196 0.8× 218 1.8× 25 0.2× 39 1.5k
H. K. Proudfit United States 17 858 1.2× 679 1.2× 311 1.3× 97 0.8× 30 0.3× 22 1.2k
Qinxue Ding China 11 298 0.4× 239 0.4× 247 1.0× 45 0.4× 56 0.5× 16 971
Karine Bon France 9 598 0.8× 314 0.5× 168 0.7× 129 1.1× 18 0.2× 11 952

Countries citing papers authored by S.S. Mokha

Since Specialization
Citations

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

Fields of papers citing papers by S.S. Mokha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S.S. Mokha

This figure shows the co-authorship network connecting the top 25 collaborators of S.S. Mokha. A scholar is included among the top collaborators of S.S. Mokha 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 S.S. Mokha. S.S. Mokha 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
4.
Small, Kersten M., Subodh Nag, & S.S. Mokha. (2013). Activation of membrane estrogen receptors attenuates opioid receptor-like1 receptor-mediated antinociception via an ERK-dependent non-genomic mechanism. Neuroscience. 255. 177–190. 27 indexed citations
5.
Nag, Subodh, et al.. (2010). Sex-specificity and estrogen-dependence of kappa opioid receptor-mediated antinociception and antihyperalgesia. Pain. 151(3). 806–815. 52 indexed citations
6.
Nag, Subodh, et al.. (2009). Estrogen-dependent, sex-specific modulation of mustard oil-induced secondary thermal hyperalgesia by orphanin FQ in the rat. Neuroscience Letters. 456(2). 59–63. 15 indexed citations
7.
Nag, Subodh & S.S. Mokha. (2009). Testosterone is essential for α2-adrenoceptor-induced antinociception in the trigeminal region of the male rat. Neuroscience Letters. 467(1). 48–52. 14 indexed citations
8.
Nag, Subodh, Qin Wang, Lee E. Limbird, & S.S. Mokha. (2008). Knockout of spinophilin, an endogenous antagonist of arrestin-dependent α2-adrenoceptor functions, enhances receptor-mediated antinociception yet does not eliminate sex-related differences. Behavioural Brain Research. 197(2). 457–461. 2 indexed citations
12.
Nag, Subodh & S.S. Mokha. (2004). Estrogen attenuates antinociception produced by stimulation of Kölliker–Fuse nucleus in the rat. European Journal of Neuroscience. 20(11). 3203–3207. 24 indexed citations
15.
Mokha, S.S., et al.. (2001). Orphanin FQ produces gender-specific modulation of trigeminal nociception: behavioral and electrophysiological observations. Neuroscience. 105(2). 489–498. 47 indexed citations
16.
19.
Mokha, S.S. & A. Iggo. (1987). Mechanisms mediating the brain stem control of somatosensory transmission in the dorsal horn of the cat's spinal cord: an intracellular analysis. Experimental Brain Research. 69(1). 93–106. 9 indexed citations
20.
Mokha, S.S. & A. Iggo. (1984). Brain stem control of spinal nociceptive transmission: An intracellular analysis of synaptic mechanisms. Pain. 18. S222–S222. 1 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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