Divya Ramnath

1.4k total citations · 1 hit paper
14 papers, 990 citations indexed

About

Divya Ramnath is a scholar working on Immunology, Molecular Biology and Cancer Research. According to data from OpenAlex, Divya Ramnath has authored 14 papers receiving a total of 990 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Immunology, 7 papers in Molecular Biology and 3 papers in Cancer Research. Recurrent topics in Divya Ramnath's work include Immune Response and Inflammation (6 papers), Immune cells in cancer (4 papers) and Histone Deacetylase Inhibitors Research (3 papers). Divya Ramnath is often cited by papers focused on Immune Response and Inflammation (6 papers), Immune cells in cancer (4 papers) and Histone Deacetylase Inhibitors Research (3 papers). Divya Ramnath collaborates with scholars based in Australia, United States and Switzerland. Divya Ramnath's co-authors include Matthew J. Sweet, Kate Schroder, Jessica B. von Pein, Petr Brož, Mercedes Monteleone, Gabriel Sollberger, Dave Boucher, Nicholas D. Condon, Kaiwen Chen and Elizabeth E. Powell and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature reviews. Immunology.

In The Last Decade

Divya Ramnath

14 papers receiving 987 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Noncanonical inflammasome signaling elicits gasdermin D–dependent neutrophil extracellular traps

2018 484 citations Kaiwen Chen, Mercedes Monteleone et al. Science Immunology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Divya Ramnath Australia	12	555	451	144	86	82	14	990
Xiwen Lou China	7	925 1.7×	376 0.8×	115 0.8×	47 0.5×	80 1.0×	7	1.1k
Pierre Guillot Germany	5	278 0.5×	442 1.0×	114 0.8×	72 0.8×	57 0.7×	6	855
Lu Cui China	16	345 0.6×	165 0.4×	94 0.7×	38 0.4×	112 1.4×	31	835
Anastasiya Hladik Austria	13	291 0.5×	613 1.4×	170 1.2×	126 1.5×	153 1.9×	26	1.0k
Chloé Abels Belgium	6	262 0.5×	569 1.3×	229 1.6×	51 0.6×	40 0.5×	6	910
Annamaria D’Aprile Italy	14	466 0.8×	163 0.4×	227 1.6×	109 1.3×	46 0.6×	21	958
Nanhong Tang China	16	440 0.8×	199 0.4×	126 0.9×	60 0.7×	63 0.8×	53	955
Tomohiko Ishibashi Japan	16	408 0.7×	237 0.5×	84 0.6×	47 0.5×	117 1.4×	58	998
Joseph A. Sennello United States	17	452 0.8×	277 0.6×	349 2.4×	130 1.5×	141 1.7×	20	1.1k

Countries citing papers authored by Divya Ramnath

Since Specialization

Citations

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

Fields of papers citing papers by Divya Ramnath

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Divya Ramnath

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

All Works

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14 of 14 papers shown

Curson, James E. B., Kaustav Das Gupta, Alun Jones, et al.. (2025). Histone deacetylase 7 mediates lipopolysaccharide-inducible mitochondrial fission in macrophages. Journal of Cell Science. 138(19). 1 indexed citations

Curson, James E. B., Divya Ramnath, Kaustav Das Gupta, et al.. (2024). Histone deacetylase 7 activates 6-phosphogluconate dehydrogenase via an enzyme-independent mechanism that involves the N-terminal protein-protein interaction domain. Biochemical Journal. 481(21). 1569–1584. 1 indexed citations

Sweet, Matthew J., Divya Ramnath, Amit Singhal, & Ronan Kapétanovic. (2024). Inducible antibacterial responses in macrophages. Nature reviews. Immunology. 25(2). 92–107. 41 indexed citations

Duszyc, Kinga, Jessica B. von Pein, Divya Ramnath, et al.. (2023). Apical extrusion prevents apoptosis from activating an acute inflammatory program in epithelia. Developmental Cell. 58(21). 2235–2248.e6. 12 indexed citations

Wang, Yizhuo, Jeffrey Y. W. Mak, Kaustav Das Gupta, et al.. (2022). Histone deacetylase 7: a signalling hub controlling development, inflammation, metabolism and disease. FEBS Journal. 290(11). 2805–2832. 39 indexed citations

Jouffe, Céline, Benjamin D. Weger, Eva Martín, et al.. (2022). Disruption of the circadian clock component BMAL1 elicits an endocrine adaption impacting on insulin sensitivity and liver disease. Proceedings of the National Academy of Sciences. 119(10). e2200083119–e2200083119. 65 indexed citations

Kapétanovic, Ronan, Divya Ramnath, Takashi Okada, et al.. (2020). Lipopolysaccharide promotes Drp1‐dependent mitochondrial fission and associated inflammatory responses in macrophages. Immunology and Cell Biology. 98(7). 528–539. 55 indexed citations

Yang, Yoon Mee, Mazen Noureddin, Cheng Liu, et al.. (2019). Hyaluronan synthase 2–mediated hyaluronan production mediates Notch1 activation and liver fibrosis. Science Translational Medicine. 11(496). 120 indexed citations

Loh, Zhixuan, Rebecca L. Fitzsimmons, Robert C. Reid, et al.. (2019). Inhibitors of class I histone deacetylases attenuate thioacetamide‐induced liver fibrosis in mice by suppressing hepatic type 2 inflammation. British Journal of Pharmacology. 176(19). 3775–3790. 25 indexed citations

10.

Ramnath, Divya, Katharine M. Irvine, Samuel W. Lukowski, et al.. (2018). Hepatic expression profiling identifies steatosis-independent and steatosis-driven advanced fibrosis genes. JCI Insight. 3(14). 33 indexed citations

11.

Chen, Kaiwen, Mercedes Monteleone, Dave Boucher, et al.. (2018). Noncanonical inflammasome signaling elicits gasdermin D–dependent neutrophil extracellular traps. Science Immunology. 3(26). 484 indexed citations breakdown →

12.

Ramnath, Divya, Elizabeth E. Powell, Glen M. Scholz, & Matthew J. Sweet. (2016). The toll-like receptor 3 pathway in homeostasis, responses to injury and wound repair. Seminars in Cell and Developmental Biology. 61. 22–30. 37 indexed citations

13.

Ramnath, Divya, Kathryn A. Tunny, Anne‐Sophie Bergot, et al.. (2015). TLR3 drives IRF6‐dependent IL‐23p19 expression and p19/EBI3 heterodimer formation in keratinocytes. Immunology and Cell Biology. 93(9). 771–779. 44 indexed citations

14.

Kwa, Mei Qi, Thao Nguyen, Jennifer Huynh, et al.. (2014). Interferon Regulatory Factor 6 Differentially Regulates Toll-like Receptor 2-dependent Chemokine Gene Expression in Epithelial Cells. Journal of Biological Chemistry. 289(28). 19758–19768. 33 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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