Sreya Bagchi

2.9k total citations · 1 hit paper
14 papers, 1.8k citations indexed

About

Sreya Bagchi is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Sreya Bagchi has authored 14 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 5 papers in Oncology and 3 papers in Molecular Biology. Recurrent topics in Sreya Bagchi's work include Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (6 papers) and CAR-T cell therapy research (4 papers). Sreya Bagchi is often cited by papers focused on Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (6 papers) and CAR-T cell therapy research (4 papers). Sreya Bagchi collaborates with scholars based in United States, Netherlands and Sweden. Sreya Bagchi's co-authors include Edgar G. Engleman, Robert Yuan, Chyung‐Ru Wang, Jie Zhao, Xiufang Weng, Ying He, Nicholas P. Cianciotto, Sha Li, Meghan M. Pearce and Hong Zhang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and The Journal of Immunology.

In The Last Decade

Sreya Bagchi

14 papers receiving 1.8k 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.

Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance

2020 1.5k citations Sreya Bagchi, Robert Yuan et al. Annual Review of Pathology Mechanisms of Disease profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sreya Bagchi United States	10	984	778	512	370	186	14	1.8k
Kim C. Ohaegbulam United States	14	1.2k 1.2×	884 1.1×	416 0.8×	339 0.9×	180 1.0×	19	1.8k
Julian A. Marin‐Acevedo United States	13	1.1k 1.2×	732 0.9×	354 0.7×	358 1.0×	151 0.8×	27	1.7k
Maria J. de Miguel Spain	20	907 0.9×	562 0.7×	566 1.1×	319 0.9×	210 1.1×	99	1.7k
Anupam M. Desai United States	7	1.3k 1.3×	870 1.1×	357 0.7×	311 0.8×	112 0.6×	11	1.9k
Lawrence P. Andrews United States	11	1.3k 1.3×	1.1k 1.5×	392 0.8×	244 0.7×	159 0.9×	14	1.9k
Saman Maleki Vareki Canada	22	1.3k 1.3×	624 0.8×	665 1.3×	418 1.1×	251 1.3×	53	2.1k
Alex Chehrazi‐Raffle United States	11	869 0.9×	461 0.6×	374 0.7×	331 0.9×	171 0.9×	64	1.3k
Max D. Wellenstein Netherlands	9	1.3k 1.3×	1.3k 1.6×	691 1.3×	307 0.8×	394 2.1×	10	2.3k
Eduardo Castañón Spain	18	1.4k 1.4×	951 1.2×	583 1.1×	453 1.2×	188 1.0×	52	2.3k
Steffen Ormanns Germany	20	1.0k 1.0×	428 0.6×	486 0.9×	315 0.9×	434 2.3×	70	1.6k

Countries citing papers authored by Sreya Bagchi

Since Specialization

Citations

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

Fields of papers citing papers by Sreya Bagchi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sreya Bagchi

This figure shows the co-authorship network connecting the top 25 collaborators of Sreya Bagchi. A scholar is included among the top collaborators of Sreya Bagchi 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 Sreya Bagchi. Sreya Bagchi 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

Bagchi, Sreya, Robert Yuan, Han-Li Huang, et al.. (2024). The acid-sensing receptor GPR65 on tumor macrophages drives tumor growth in obesity. Science Immunology. 9(100). eadg6453–eadg6453. 10 indexed citations

Bagchi, Sreya, Jeegar Patel, & Jamie L. Harden. (2024). Transcriptional profiling of primary human-skin derived mast cell activation by various MRGPRX2 agonists and inhibition with EVO756. The Journal of Immunology. 212(1_Supplement). 0721_7011–0721_7011. 1 indexed citations

Yuan, Robert, Nupur Bhattacharya, Justin A. Kenkel, et al.. (2020). Enteric Glia Play a Critical Role in Promoting the Development of Colorectal Cancer. Frontiers in Oncology. 10. 595892–595892. 25 indexed citations

Reticker-Flynn, Nathan E., Weiruo Zhang, Pamela A. Basto, et al.. (2020). Lymph Node Colonization Alters the Systemic Immune Response to Enable Metastasis to Distant Tissues. SSRN Electronic Journal. 1 indexed citations

Bagchi, Sreya, Robert Yuan, & Edgar G. Engleman. (2020). Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. Annual Review of Pathology Mechanisms of Disease. 16(1). 223–249. 1478 indexed citations breakdown →

Bagchi, Sreya, et al.. (2018). Linking CD1-Restricted T Cells With Autoimmunity and Dyslipidemia: Lipid Levels Matter. Frontiers in Immunology. 9. 1616–1616. 23 indexed citations

Bagchi, Sreya, Ying He, Hong Zhang, et al.. (2017). CD1b-autoreactive T cells contribute to hyperlipidemia-induced skin inflammation in mice. Journal of Clinical Investigation. 127(6). 2339–2352. 50 indexed citations

Bagchi, Sreya, Sha Li, & Chyung‐Ru Wang. (2016). CD1b-autoreactive T cells recognize phospholipid antigens and contribute to antitumor immunity against a CD1b⁺T cell lymphoma. OncoImmunology. 5(9). e1213932–e1213932. 24 indexed citations

Zhao, Jie, Sarah Siddiqui, Shaobin Shang, et al.. (2015). Mycolic acid-specific T cells protect against Mycobacterium tuberculosis infection in a humanized transgenic mouse model. eLife. 4. 42 indexed citations

10.

Bagchi, Sreya, Hong Zhang, Ying He, & Chyung‐Ru Wang. (2015). Self-lipid specific T cells, restricted by CD1b, contribute to the development of hyperlipidemia-associated skin inflammation (BA11P.133). The Journal of Immunology. 194(1_Supplement). 184.15–184.15. 1 indexed citations

11.

Zhao, Jie, Sreya Bagchi, & Chyung‐Ru Wang. (2014). Type II natural killer T cells foster the antitumor activity of CpG-oligodeoxynucleotides. OncoImmunology. 3(5). e28977–e28977. 6 indexed citations

12.

Weng, Xiufang, et al.. (2014). The adaptor protein SAP regulates type II NKT‐cell development, cytokine production, and cytotoxicity against lymphoma. European Journal of Immunology. 44(12). 3646–3657. 10 indexed citations

13.

Zhao, Jie, Xiufang Weng, Sreya Bagchi, & Chyung‐Ru Wang. (2014). Polyclonal type II natural killer T cells require PLZF and SAP for their development and contribute to CpG-mediated antitumor response. Proceedings of the National Academy of Sciences. 111(7). 2674–2679. 57 indexed citations

14.

Pearce, Meghan M., et al.. (2013). Multiple Legionella pneumophila Type II Secretion Substrates, Including a Novel Protein, Contribute to Differential Infection of the Amoebae Acanthamoeba castellanii, Hartmannella vermiformis, and Naegleria lovaniensis. Infection and Immunity. 81(5). 1399–1410. 49 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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