Mrinal K. Poddar

898 total citations
82 papers, 679 citations indexed

About

Mrinal K. Poddar is a scholar working on Physiology, Cellular and Molecular Neuroscience and Pharmacology. According to data from OpenAlex, Mrinal K. Poddar has authored 82 papers receiving a total of 679 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Physiology, 26 papers in Cellular and Molecular Neuroscience and 25 papers in Pharmacology. Recurrent topics in Mrinal K. Poddar's work include Biochemical effects in animals (30 papers), Neuroscience and Neuropharmacology Research (23 papers) and Cannabis and Cannabinoid Research (18 papers). Mrinal K. Poddar is often cited by papers focused on Biochemical effects in animals (30 papers), Neuroscience and Neuropharmacology Research (23 papers) and Cannabis and Cannabinoid Research (18 papers). Mrinal K. Poddar collaborates with scholars based in India, United States and Italy. Mrinal K. Poddar's co-authors include William L. Dewey, Soumyabrata Banerjee, J. J. Ghosh, Bidhan C. Bandyopadhyay, Subir K. Ray, Gopa Mitra, Somnath Mukhopadhyay, Biswajit Mukherjee, Jagat J. Ghosh and Debasmita Dutta and has published in prestigious journals such as Brain Research, Neuroscience and Journal of Neurochemistry.

In The Last Decade

Mrinal K. Poddar

79 papers receiving 645 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mrinal K. Poddar India 14 212 200 186 107 68 82 679
Yung‐Hi Kim South Korea 17 134 0.6× 292 1.5× 180 1.0× 293 2.7× 52 0.8× 28 819
Yogita Mundhada India 14 216 1.0× 135 0.7× 230 1.2× 252 2.4× 67 1.0× 18 794
Pankaj Dixit India 16 230 1.1× 123 0.6× 226 1.2× 285 2.7× 62 0.9× 36 965
Paula Lunardi Brazil 16 184 0.9× 130 0.7× 192 1.0× 184 1.7× 46 0.7× 26 720
Abolhasan Ahmadiani Iran 16 146 0.7× 220 1.1× 228 1.2× 160 1.5× 42 0.6× 36 831
Bernd Moosmann Germany 10 123 0.6× 233 1.2× 101 0.5× 330 3.1× 33 0.5× 13 899
Terry D. Lindstrom United States 14 218 1.0× 84 0.4× 327 1.8× 245 2.3× 105 1.5× 43 979
Sudhir N. Umathe India 18 217 1.0× 108 0.5× 315 1.7× 178 1.7× 96 1.4× 38 838
Dorota Nieoczym Poland 20 210 1.0× 200 1.0× 383 2.1× 366 3.4× 51 0.8× 54 1.1k
Kulkarni Sk India 15 86 0.4× 73 0.4× 237 1.3× 160 1.5× 46 0.7× 68 566

Countries citing papers authored by Mrinal K. Poddar

Since Specialization
Citations

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

Fields of papers citing papers by Mrinal K. Poddar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mrinal K. Poddar. 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 Mrinal K. Poddar. The network helps show where Mrinal K. Poddar may publish in the future.

Co-authorship network of co-authors of Mrinal K. Poddar

This figure shows the co-authorship network connecting the top 25 collaborators of Mrinal K. Poddar. A scholar is included among the top collaborators of Mrinal K. Poddar 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 Mrinal K. Poddar. Mrinal K. Poddar 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.
Poddar, Mrinal K., Aundy Kumar, Aditi Kundu, et al.. (2025). Pectin and starch- based composite coating functionalized with snake plant (Dracaena trifasciata) extract: Shelf-life extension and suppression of anthracnose in banana. South African Journal of Botany. 183. 167–178.
2.
Banerjee, Soumyabrata & Mrinal K. Poddar. (2020). Carnosine research in relation to aging brain and neurodegeneration: A blessing for geriatrics and their neuronal disorders. Archives of Gerontology and Geriatrics. 91. 104239–104239. 15 indexed citations
3.
Banerjee, Soumyabrata & Mrinal K. Poddar. (2016). Aging-induced changes in brain regional serotonin receptor binding: Effect of Carnosine. Neuroscience. 319. 79–91. 10 indexed citations
4.
Banerjee, Soumyabrata, Tushar K. Ghosh, & Mrinal K. Poddar. (2015). Carnosine reverses the aging-induced down regulation of brain regional serotonergic system. Mechanisms of Ageing and Development. 152. 5–14. 10 indexed citations
5.
Banerjee, Soumyabrata & Mrinal K. Poddar. (2013). Platelet monoamine oxidase-A activity and aging: effect of carnosine. The Journal of Physiological Sciences. 63(4). 279–285. 8 indexed citations
7.
Poddar, Mrinal K., et al.. (2008). Dietary protein–carbohydrate ratio: Exogenous modulator of immune response with age. Immunobiology. 213(7). 557–566. 9 indexed citations
8.
Poddar, Mrinal K., et al.. (2008). Long-Term Caffeine Consumption Reverses Tumor-Induced Suppression of the Innate Immune Response in Adult Mice. Planta Medica. 74(15). 1779–1784. 9 indexed citations
9.
Pal, Sudipta & Mrinal K. Poddar. (2007). Long-term Exposure of Variable Dietary Protein-to-Carbohydrate Ratio: Effect on Brain Regional Glutamatergic Activity with Age. Neurochemical Research. 33(5). 952–961. 4 indexed citations
10.
Pal, Sudipta, et al.. (2006). Dietary variation of protein–carbohydrate: Effect on hypothalamic and hippocampal GABA–glutamate in relation to aging. Nutritional Neuroscience. 9(5-6). 241–249. 3 indexed citations
11.
Chakrabarti, Lina, Bidhan C. Bandyopadhyay, & Mrinal K. Poddar. (2001). Age-Associated Hypothalamic Glutamate Receptor Density: Effect of Dietary Protein. Neurochemical Research. 26(2). 145–151. 1 indexed citations
12.
Poddar, Mrinal K., et al.. (2001). Role of Brain Regional GABA: Aldrin-Induced Stimulation of Locomotor Activity in Rat. Neurochemical Research. 26(4). 439–451. 4 indexed citations
13.
Bandyopadhyay, Bidhan C. & Mrinal K. Poddar. (1998). Hypothalamic GABA-ergic activity and T-cell proliferation in aged mammal: effect of dietary protein. Neurochemistry International. 32(2). 191–196. 9 indexed citations
14.
Bandyopadhyay, Bidhan C. & Mrinal K. Poddar. (1998). Dietary protein-induced change in mammalian corticosterone status (index of immune response) during aging. Mechanisms of Ageing and Development. 103(1). 57–68. 6 indexed citations
15.
Bandyopadhyay, Bidhan C. & Mrinal K. Poddar. (1997). Is Hypothalamic GABA Involved in Immune Function in Relation to Dietary Protein During Aging?. Neurochemical Research. 22(9). 1135–1144. 7 indexed citations
16.
Poddar, Mrinal K., et al.. (1992). Effect of δ-9-tetrahydrocannabinol and theophylline on hepatic microsomal drug metabolizing enzymes. Biochemical Pharmacology. 44(10). 2021–2027. 2 indexed citations
17.
Ray, Subir K. & Mrinal K. Poddar. (1990). Interaction of central serotonin and dopamine in the regulation of carbaryl-iduced tremor. European Journal of Pharmacology. 181(3). 159–166. 10 indexed citations
18.
Poddar, Mrinal K., et al.. (1990). In vivo and in vitro effects of aldrin on rat brain synaptosomal Mg2+ and Na+,K+-adenosine triphosphatase. Biochemical Pharmacology. 40(7). 1449–1456. 2 indexed citations
19.
Ghosh, Saswati & Mrinal K. Poddar. (1989). Fatty acids and cholesterol: effect on the interaction of theophylline with bovine serum albumin. International Journal of Biological Macromolecules. 11(5). 303–306. 1 indexed citations
20.
Poddar, Mrinal K.. (1987). Interaction of theophylline with bovine serum albumin. Medical science research. 15(17). 1027–1028. 2 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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