Sumit Sarkar

4.3k total citations · 1 hit paper
91 papers, 3.4k citations indexed

About

Sumit Sarkar is a scholar working on Physiology, Endocrine and Autonomic Systems and Cellular and Molecular Neuroscience. According to data from OpenAlex, Sumit Sarkar has authored 91 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Physiology, 24 papers in Endocrine and Autonomic Systems and 23 papers in Cellular and Molecular Neuroscience. Recurrent topics in Sumit Sarkar's work include Alzheimer's disease research and treatments (21 papers), Regulation of Appetite and Obesity (18 papers) and Neuroinflammation and Neurodegeneration Mechanisms (12 papers). Sumit Sarkar is often cited by papers focused on Alzheimer's disease research and treatments (21 papers), Regulation of Appetite and Obesity (18 papers) and Neuroinflammation and Neurodegeneration Mechanisms (12 papers). Sumit Sarkar collaborates with scholars based in United States, Hungary and India. Sumit Sarkar's co-authors include Ronald M. Lechan, James Raymick, Csaba Fekete, Jason Chung, Allen Lu, Duyu Nie, Lale Özcan, Umut Özcan, Martin G. Myers and Larry Schmued and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cell Metabolism and Brain Research.

In The Last Decade

Sumit Sarkar

88 papers receiving 3.4k citations

Hit Papers

Endoplasmic Reticulum Stress Plays a Central Role in Deve... 2009 2026 2014 2020 2009 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sumit Sarkar United States 30 1.3k 1.1k 663 594 531 91 3.4k
Jia Yu China 27 956 0.8× 852 0.8× 1.7k 2.6× 630 1.1× 662 1.2× 93 4.2k
Ewan C. McNay United States 33 1.3k 1.0× 1.6k 1.4× 1.1k 1.7× 663 1.1× 1.0k 1.9× 55 4.5k
Qingchun Tong United States 38 2.1k 1.7× 1.5k 1.4× 935 1.4× 796 1.3× 803 1.5× 101 4.5k
Daniela Giuliani Italy 35 650 0.5× 513 0.5× 726 1.1× 353 0.6× 730 1.4× 127 3.5k
Michael L. Niehoff United States 28 540 0.4× 937 0.9× 840 1.3× 379 0.6× 510 1.0× 76 2.8k
Minho Moon South Korea 38 596 0.5× 1.6k 1.4× 1.3k 2.0× 365 0.6× 855 1.6× 111 4.0k
Dinesh Gautam United States 25 1.1k 0.9× 1.4k 1.3× 2.1k 3.1× 415 0.7× 1.3k 2.4× 29 4.7k
Nils Wierup Sweden 41 1.2k 1.0× 1.3k 1.2× 1.7k 2.6× 667 1.1× 1.3k 2.5× 118 5.3k
Jianguo Li United States 33 1.1k 0.9× 2.3k 2.1× 1.0k 1.5× 180 0.3× 624 1.2× 87 4.1k
Kelvin A. Yamada United States 34 928 0.7× 2.7k 2.5× 2.0k 3.0× 613 1.0× 1.7k 3.3× 49 5.7k

Countries citing papers authored by Sumit Sarkar

Since Specialization
Citations

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

Fields of papers citing papers by Sumit Sarkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sumit Sarkar

This figure shows the co-authorship network connecting the top 25 collaborators of Sumit Sarkar. A scholar is included among the top collaborators of Sumit Sarkar 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 Sumit Sarkar. Sumit Sarkar 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.
Gokulan, Kuppan, et al.. (2025). Potential link of high fat diet and mRNA expression of Alzheimer's disease-related genes in the enteric mucosa of a rat model of Alzheimer's disease. Journal of Alzheimer s Disease Reports. 9. 4133475022–4133475022.
2.
Sur, Tapas Kumar, Gail Nunlee‐Bland, Christopher A. Loffredo, et al.. (2025). Developing non-invasive molecular markers for early risk assessment of Alzheimer's disease. PubMed. 12. 100120–100120. 1 indexed citations
3.
Sarkar, Sumit, Partha Pratim Ghosh, Sumi Ganguly, et al.. (2024). Insights into biomimetic system–ligand interaction of substituted isophthalic acid: A functionality induced photophysical study. Photochemistry and Photobiology. 101(1). 116–132. 2 indexed citations
4.
Sarkar, Sumit, et al.. (2023). The role of astrocytes in the glymphatic network: a narrative review. Metabolic Brain Disease. 39(3). 453–465. 7 indexed citations
5.
Liachenko, Serguei, et al.. (2021). Global Neurotoxicity: Quantitative Analysis of Rat Brain Toxicity Following Exposure to Trimethyltin. International Journal of Toxicology. 40(4). 367–379. 3 indexed citations
6.
Liachenko, Serguei, Sumit Sarkar, Merle G. Paule, et al.. (2020). Quantitative Neurotoxicology: An Assessment of the Neurotoxic Profile of Kainic Acid in Sprague Dawley Rats. International Journal of Toxicology. 39(4). 294–306. 9 indexed citations
10.
Bowyer, John F., Sumit Sarkar, Nysia I. George, et al.. (2017). Corticosterone and exogenous glucose alter blood glucose levels, neurotoxicity, and vascular toxicity produced by methamphetamine. Journal of Neurochemistry. 143(2). 198–213. 16 indexed citations
11.
Eitan, Erez, Emmette R. Hutchison, Nigel H. Greig, et al.. (2015). Combination therapy with lenalidomide and nanoceria ameliorates CNS autoimmunity. Experimental Neurology. 273. 151–160. 39 indexed citations
12.
Gu, Qiang, Susan M. Lantz, Héctor Rosas-Hernández, et al.. (2014). In vitro detection of cytotoxicity using FluoroJade-C. Toxicology in Vitro. 28(4). 469–472. 11 indexed citations
13.
Hanig, Joseph P., Merle G. Paule, Jaivijay Ramu, et al.. (2014). The use of MRI to assist the section selections for classical pathology assessment of neurotoxicity. Regulatory Toxicology and Pharmacology. 70(3). 641–647. 22 indexed citations
14.
Schmued, Larry, et al.. (2013). Characterization of Myelin Pathology in the Hippocampal Complex of a Transgenic Mouse Model of Alzheimer’s Disease. Current Alzheimer Research. 10(1). 30–37. 27 indexed citations
15.
Zhang, Yihong, James Raymick, Sumit Sarkar, et al.. (2013). Efficacy and Toxicity of Clioquinol Treatment and A-beta42 Inoculation in the APP/PSI Mouse Model of Alzheimer’s Disease. Current Alzheimer Research. 10(5). 494–506. 30 indexed citations
16.
Sarkar, Sumit, James Raymick, & Larry Schmued. (2012). Temporal Progression of Kainic Acid Induced Changes in Vascular Laminin Expression in Rat Brain with Neuronal and Glial Correlates. Current Neurovascular Research. 9(2). 110–119. 7 indexed citations
17.
Zaretsky, Dmitry V., et al.. (2009). Dorsomedial hypothalamus mediates autonomic, neuroendocrine, and locomotor responses evoked from the medial preoptic area. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. 298(1). R130–R140. 34 indexed citations
18.
Özcan, Lale, Allen Lu, Jason Chung, et al.. (2009). Endoplasmic Reticulum Stress Plays a Central Role in Development of Leptin Resistance. Cell Metabolism. 9(1). 35–51. 713 indexed citations breakdown →
19.
Zaretskaia, Maria V., Dmitry V. Zaretsky, Sumit Sarkar, Anantha Shekhar, & Joseph A. DiMicco. (2008). Induction of Fos-immunoreactivity in the rat brain following disinhibition of the dorsomedial hypothalamus. Brain Research. 1200. 39–50. 36 indexed citations
20.
Sarkar, Sumit & Nishikant K. Subhedar. (2001). Glucagon-like Immunoreactivity in the Forebrain and Pituitary of the Teleost, Clarias batrachus (Linn.). General and Comparative Endocrinology. 121(1). 23–31. 6 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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