Debanjan Dhar

5.4k total citations · 5 hit papers
32 papers, 3.1k citations indexed

About

Debanjan Dhar is a scholar working on Molecular Biology, Epidemiology and Oncology. According to data from OpenAlex, Debanjan Dhar has authored 32 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 12 papers in Epidemiology and 10 papers in Oncology. Recurrent topics in Debanjan Dhar's work include Liver Disease Diagnosis and Treatment (11 papers), Virus-based gene therapy research (9 papers) and Liver physiology and pathology (7 papers). Debanjan Dhar is often cited by papers focused on Liver Disease Diagnosis and Treatment (11 papers), Virus-based gene therapy research (9 papers) and Liver physiology and pathology (7 papers). Debanjan Dhar collaborates with scholars based in United States, Japan and China. Debanjan Dhar's co-authors include Michael Karin, David A. Brenner, Tatiana Kisseleva, William S.M. Wold, Károly Tóth, Joan Font-Burgada, Jacopo Baglieri, Jacqueline F. Spencer, Hayato Nakagawa and Zhenyu Zhong and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Debanjan Dhar

31 papers receiving 3.1k citations

Hit Papers

5 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.

Immunosuppressive plasma cells impede T-cell-dependent immunogenic chemotherapy

2015 429 citations Shabnam Shalapour, Joan Font-Burgada et al. Nature profile →
ER Stress Cooperates with Hypernutrition to Trigger TNF-Dependent Spontaneous HCC Development

2014 396 citations Hayato Nakagawa, Atsushi Umemura et al. Cancer Cell profile →
Mechanisms of liver fibrosis and its role in liver cancer

2020 287 citations Debanjan Dhar, Jacopo Baglieri et al. profile →
ER Stress Drives Lipogenesis and Steatohepatitis via Caspase-2 Activation of S1P

2018 246 citations Ju Youn Kim, Ricard Garcia‐Carbonell et al. Cell profile →
Lipid-associated macrophages’ promotion of fibrosis resolution during MASH regression requires TREM2

2024 46 citations Souradipta Ganguly, Sara Brin Rosenthal et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Debanjan Dhar United States	22	1.2k	1.1k	883	650	641	32	3.1k
Hisanobu Ogata Japan	16	1.1k 0.9×	1.0k 0.9×	863 1.0×	716 1.1×	607 0.9×	26	3.0k
Ryotaro Sakamori Japan	27	790 0.7×	838 0.8×	556 0.6×	561 0.9×	648 1.0×	107	2.4k
Wen Yang China	26	1.9k 1.6×	516 0.5×	1.1k 1.2×	569 0.9×	633 1.0×	71	3.7k
María J. Perugorria Spain	25	1.1k 0.9×	557 0.5×	582 0.7×	610 0.9×	251 0.4×	52	2.6k
Joan Font-Burgada United States	15	1.0k 0.9×	587 0.5×	852 1.0×	493 0.8×	799 1.2×	20	2.6k
Linda Hammerich Germany	24	653 0.5×	919 0.9×	666 0.8×	778 1.2×	1.3k 2.0×	51	2.9k
Hayato Hikita Japan	29	1.7k 1.4×	1.4k 1.3×	600 0.7×	842 1.3×	492 0.8×	133	3.6k
Dianne H. Dapito United States	17	1.3k 1.1×	2.2k 2.0×	590 0.7×	2.0k 3.1×	735 1.1×	18	4.3k
Henning Schulze‐Bergkamen Germany	31	1.8k 1.5×	676 0.6×	995 1.1×	607 0.9×	468 0.7×	70	3.2k
Minnie Y.Y. Go Hong Kong	31	1.2k 1.0×	718 0.7×	362 0.4×	441 0.7×	232 0.4×	41	2.6k

Countries citing papers authored by Debanjan Dhar

Since Specialization

Citations

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

Fields of papers citing papers by Debanjan Dhar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debanjan Dhar

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

All Works

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20 of 20 papers shown

Spann, Nathanael J., Wenxi Tang, Fenghua Zeng, et al.. (2025). Genetic variation in the activity of a TREM2–p53 signaling axis determines oxygen-induced lung injury. Nature Immunology. 26(8). 1287–1298.

Rohm, Theresa V., Felipe C.G. Reis, Karina Cunha e Rocha, et al.. (2025). Adipose Tissue Macrophages in Metabolic Dysfunction–Associated Steatohepatitis Secrete Extracellular Vesicles That Activate Liver Fibrosis in Obese Male Mice. Gastroenterology. 169(4). 691–704.e9. 3 indexed citations

Ganguly, Souradipta, Sara Brin Rosenthal, Ty D. Troutman, et al.. (2024). Lipid-associated macrophages’ promotion of fibrosis resolution during MASH regression requires TREM2. Proceedings of the National Academy of Sciences. 121(35). e2405746121–e2405746121. 46 indexed citations breakdown →

Baglieri, Jacopo, Cuili Zhang, Shuang Liang, et al.. (2021). Nondegradable Collagen Increases Liver Fibrosis but Not Hepatocellular Carcinoma in Mice. American Journal Of Pathology. 191(9). 1564–1579. 14 indexed citations

Rosenthal, Sara Brin, Xiao Liu, Souradipta Ganguly, et al.. (2021). Heterogeneity of HSCs in a Mouse Model of NASH. Hepatology. 74(2). 667–685. 100 indexed citations

Kim, Young Chul, Souradipta Ganguly, Josselin Nespoux, et al.. (2020). Western Diet Promotes Renal Injury, Inflammation, and Fibrosis in a Murine Model of Alström Syndrome. The Nephron journals/Nephron journals. 144(8). 400–412. 4 indexed citations

Nishio, Takahiro, Yukinori Koyama, Shuang Liang, et al.. (2019). Activated hepatic stellate cells and portal fibroblasts contribute to cholestatic liver fibrosis in MDR2 knockout mice. Journal of Hepatology. 71(3). 573–585. 98 indexed citations

Kim, Ju Youn, Ricard Garcia‐Carbonell, Shinichiro Yamachika, et al.. (2018). ER Stress Drives Lipogenesis and Steatohepatitis via Caspase-2 Activation of S1P. Cell. 175(1). 133–145.e15. 246 indexed citations breakdown →

Dhar, Debanjan, Laura Antonucci, Hayato Nakagawa, et al.. (2018). Liver Cancer Initiation Requires p53 Inhibition by CD44-Enhanced Growth Factor Signaling. Cancer Cell. 33(6). 1061–1077.e6. 156 indexed citations

10.

Liang, Shuang, Zhenyu Zhong, Debanjan Dhar, et al.. (2018). NADPH Oxidase 1 in Liver Macrophages Promotes Inflammation and Tumor Development in Mice. Gastroenterology. 156(4). 1156–1172.e6. 76 indexed citations

11.

Todoric, Jelena, Laura Antonucci, Giuseppe Di, et al.. (2017). Stress-Activated NRF2-MDM2 Cascade Controls Neoplastic Progression in Pancreas. Cancer Cell. 32(6). 824–839.e8. 109 indexed citations

12.

Karin, Michael & Debanjan Dhar. (2016). Liver carcinogenesis: from naughty chemicals to soothing fat and the surprising role of NRF2. Carcinogenesis. 37(6). 541–546. 52 indexed citations

13.

Shalapour, Shabnam, Joan Font-Burgada, Giuseppe Di, et al.. (2015). Immunosuppressive plasma cells impede T-cell-dependent immunogenic chemotherapy. Nature. 521(7550). 94–98. 429 indexed citations breakdown →

14.

Nakagawa, Hayato, Yohko Hikiba, Yoshihiro Hirata, et al.. (2014). Loss of liver E-cadherin induces sclerosing cholangitis and promotes carcinogenesis. Proceedings of the National Academy of Sciences. 111(3). 1090–1095. 95 indexed citations

15.

Dhar, Debanjan, Károly Tóth, & William S.M. Wold. (2014). Cycles of transient high-dose cyclophosphamide administration and intratumoral oncolytic adenovirus vector injection for long-term tumor suppression in Syrian hamsters. Cancer Gene Therapy. 21(4). 171–178. 15 indexed citations

16.

Nakagawa, Hayato, Atsushi Umemura, Koji Taniguchi, et al.. (2014). ER Stress Cooperates with Hypernutrition to Trigger TNF-Dependent Spontaneous HCC Development. Cancer Cell. 26(3). 331–343. 396 indexed citations breakdown →

17.

Dhar, Debanjan, Károly Tóth, & William S.M. Wold. (2011). Syrian Hamster Tumor Model to Study Oncolytic Ad5-Based Vectors. Methods in molecular biology. 797. 53–63. 15 indexed citations

18.

Tóth, Károly, Debanjan Dhar, & William S.M. Wold. (2010). Oncolytic (replication-competent) adenoviruses as anticancer agents. Expert Opinion on Biological Therapy. 10(3). 353–368. 45 indexed citations

19.

Ying, Baoling, Károly Tóth, Jacqueline F. Spencer, et al.. (2009). INGN 007, an oncolytic adenovirus vector, replicates in Syrian hamsters but not mice: comparison of biodistribution studies. Cancer Gene Therapy. 16(8). 625–637. 47 indexed citations

20.

Dhar, Debanjan, Jacqueline F. Spencer, Károly Tóth, & William S.M. Wold. (2009). Pre-existing Immunity and Passive Immunity to Adenovirus 5 Prevents Toxicity Caused by an Oncolytic Adenovirus Vector in the Syrian Hamster Model. Molecular Therapy. 17(10). 1724–1732. 35 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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