Sumana Chakravarty

7.8k total citations · 1 hit paper
100 papers, 4.3k citations indexed

About

Sumana Chakravarty is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Neurology. According to data from OpenAlex, Sumana Chakravarty has authored 100 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 20 papers in Cellular and Molecular Neuroscience and 14 papers in Neurology. Recurrent topics in Sumana Chakravarty's work include Neuroinflammation and Neurodegeneration Mechanisms (14 papers), Stress Responses and Cortisol (12 papers) and Neurotransmitter Receptor Influence on Behavior (9 papers). Sumana Chakravarty is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (14 papers), Stress Responses and Cortisol (12 papers) and Neurotransmitter Receptor Influence on Behavior (9 papers). Sumana Chakravarty collaborates with scholars based in India, United States and France. Sumana Chakravarty's co-authors include Miles Herkenham, Arvind Kumar, Eric J. Nestler, Colleen A. McClung, Scott J. Russo, Vaishnav Krishnan, Ami Graham, Shari G. Birnbaum, Bommana Raghunath Reddy and Vincent Vialou and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Journal of Neuroscience.

In The Last Decade

Sumana Chakravarty

96 papers receiving 4.2k citations

Hit Papers

Mania-like behavior induced by disruption of CLOCK 2007 2026 2013 2019 2007 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
Sumana Chakravarty India 32 1.3k 944 703 615 570 100 4.3k
Hirotaka Shoji Japan 32 1.1k 0.8× 879 0.9× 254 0.4× 610 1.0× 340 0.6× 75 3.4k
Tim Karl Australia 42 1.3k 1.0× 2.1k 2.3× 480 0.7× 377 0.6× 506 0.9× 127 5.0k
Ai‐Min Bao China 32 646 0.5× 503 0.5× 621 0.9× 1.4k 2.2× 802 1.4× 74 3.8k
Ute Krügel Germany 35 1.1k 0.8× 751 0.8× 813 1.2× 226 0.4× 420 0.7× 85 3.8k
Iiris Hovatta Finland 38 1.6k 1.2× 702 0.7× 347 0.5× 523 0.9× 536 0.9× 92 4.6k
Árpád Dobolyi Hungary 33 1.1k 0.8× 1.1k 1.1× 487 0.7× 218 0.4× 216 0.4× 129 3.2k
Rainald Mößner Germany 37 1.6k 1.2× 2.1k 2.2× 218 0.3× 647 1.1× 714 1.3× 99 5.2k
Michel Goiny Sweden 36 1.4k 1.1× 1.8k 1.9× 453 0.6× 453 0.7× 634 1.1× 104 4.5k
Tatyana Strekalova Russia 36 964 0.8× 1.1k 1.2× 243 0.3× 1.5k 2.5× 1.1k 2.0× 126 4.4k
Artur H. Świergiel United States 34 697 0.5× 694 0.7× 358 0.5× 1.7k 2.7× 1.0k 1.8× 90 3.9k

Countries citing papers authored by Sumana Chakravarty

Since Specialization
Citations

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

Fields of papers citing papers by Sumana Chakravarty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sumana Chakravarty

This figure shows the co-authorship network connecting the top 25 collaborators of Sumana Chakravarty. A scholar is included among the top collaborators of Sumana Chakravarty 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 Sumana Chakravarty. Sumana Chakravarty 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
2.
Patel, Shashikant, et al.. (2025). Modeling vicarious social defeat stress in rodents for investigating emotional stress-induced depression. Journal of Psychiatric Research. 190. 52–68. 1 indexed citations
3.
Patel, Shashikant, et al.. (2024). From blood to brain: Exploring the role of fibrinogen in the pathophysiology of depression and other neurological disorders. International Immunopharmacology. 143(Pt 1). 113326–113326. 4 indexed citations
5.
Patel, Shashikant & Sumana Chakravarty. (2024). HDAC Dynamics and GR Signaling: Neurobiological Insights and Antidepressant Potential. 4(1). 57–62.
6.
Kumar, Arvind, et al.. (2024). Cerebral stroke-induced neurogenesis: insights and therapeutic implications. SHILAP Revista de lepidopterología. 172–197. 3 indexed citations
7.
Chakravarty, Sumana, et al.. (2024). One flask cascade approach to a complex pyrano[2,3-c]pyrazole-pyrazolone hybrid heterocyclic system and its initiatory neurobiological profiling. Chemical Communications. 60(64). 8443–8446. 1 indexed citations
8.
Roy, Arpita, et al.. (2023). Therapeutic potentials of terbium hydroxide nanorods for amelioration of hypoxia-reperfusion injury in cardiomyocytes. Biomaterials Advances. 153. 213531–213531. 5 indexed citations
9.
Sreeja, V., et al.. (2023). Pharmacogenetics of selective serotonin reuptake inhibitors (SSRI): A serotonin reuptake transporter (SERT)-based approach. Neurochemistry International. 173. 105672–105672. 7 indexed citations
10.
Athira, K V, et al.. (2020). Rapid acting antidepressants in the mTOR pathway: Current evidence. Brain Research Bulletin. 163. 170–177. 25 indexed citations
11.
Elechalawar, Chandra Kumar, Dwaipayan Bhattacharya, Piyush Chaturbedy, et al.. (2019). Dual targeting of folate receptor-expressing glioma tumor-associated macrophages and epithelial cells in the brain using a carbon nanosphere–cationic folate nanoconjugate. Nanoscale Advances. 1(9). 3555–3567. 41 indexed citations
12.
Athira, K V, et al.. (2019). An Overview of the Heterogeneity of Major Depressive Disorder: Current Knowledge and Future Prospective. Current Neuropharmacology. 18(3). 168–187. 68 indexed citations
14.
Maitra, Swati, Marylène Chollet‐Krugler, Sophie Tomasi, et al.. (2016). Lichen-derived compounds show potential for central nervous system therapeutics. Phytomedicine. 23(12). 1527–1534. 38 indexed citations
15.
Chakravarty, Sumana, Priya Jhelum, Wenson D. Rajan, et al.. (2016). Insights into the epigenetic mechanisms involving histone lysine methylation and demethylation in ischemia induced damage and repair has therapeutic implication. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1863(1). 152–164. 33 indexed citations
16.
Gaspari, Sevasti, Ja Wook Koo, Rosemary C. Bagot, et al.. (2014). Nucleus Accumbens-Specific Interventions in RGS9-2 Activity Modulate Responses to Morphine. Neuropsychopharmacology. 39(8). 1968–1977. 36 indexed citations
17.
Allen, Patrick B., Sumana Chakravarty, Ivone Gomes, et al.. (2008). Multiple Actions of Spinophilin Regulate Mu Opioid Receptor Function. Neuron. 58(2). 238–247. 58 indexed citations
18.
Roybal, Kole T., Ami Graham, Jennifer A. DiNieri, et al.. (2007). Mania-like behavior induced by disruption of CLOCK. Proceedings of the National Academy of Sciences. 104(15). 6406–6411. 617 indexed citations breakdown →
19.
Chakravarty, Sumana & Miles Herkenham. (2005). Toll-Like Receptor 4 on Nonhematopoietic Cells Sustains CNS Inflammation during Endotoxemia, Independent of Systemic Cytokines. Journal of Neuroscience. 25(7). 1788–1796. 323 indexed citations
20.
Valentine, Gerald, Sumana Chakravarty, John M. Sarvey, Clive R. Bramham, & Miles Herkenham. (2000). Fragile X (fmr1) mRNA expression is differentially regulated in two adult models of activity-dependent gene expression. Molecular Brain Research. 75(2). 337–341. 19 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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