Ankit Tanwar

540 total citations
22 papers, 369 citations indexed

About

Ankit Tanwar is a scholar working on Molecular Biology, Pharmacology and Immunology. According to data from OpenAlex, Ankit Tanwar has authored 22 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Pharmacology and 5 papers in Immunology. Recurrent topics in Ankit Tanwar's work include Glycosylation and Glycoproteins Research (5 papers), Essential Oils and Antimicrobial Activity (5 papers) and Pharmacological Effects of Natural Compounds (4 papers). Ankit Tanwar is often cited by papers focused on Glycosylation and Glycoproteins Research (5 papers), Essential Oils and Antimicrobial Activity (5 papers) and Pharmacological Effects of Natural Compounds (4 papers). Ankit Tanwar collaborates with scholars based in United States, India and China. Ankit Tanwar's co-authors include Ankita Singh Chakotiya, Alka Narula, Rakesh Kumar Sharma, Xingxing Zang, Pallavi Thakur, Raman Chawla, Rajesh Arora, Rajeev K. Goel, Pamela Stanley and Anne Tranberg Madsen and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and The FASEB Journal.

In The Last Decade

Ankit Tanwar

21 papers receiving 364 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ankit Tanwar United States 11 131 108 68 57 51 22 369
Chiung‐Hung Chang Taiwan 12 138 1.1× 66 0.6× 53 0.8× 49 0.9× 60 1.2× 16 617
Jiaqi Huang China 14 274 2.1× 91 0.8× 86 1.3× 43 0.8× 111 2.2× 49 696
Jacinto da Costa Silva Neto Brazil 16 164 1.3× 61 0.6× 121 1.8× 136 2.4× 57 1.1× 42 590
Khan Farheen Badrealam India 12 213 1.6× 34 0.3× 45 0.7× 44 0.8× 24 0.5× 25 422
Yingfang Guo China 16 232 1.8× 93 0.9× 45 0.7× 43 0.8× 174 3.4× 25 631
Chooi Ling Lim Malaysia 12 210 1.6× 39 0.4× 49 0.7× 46 0.8× 31 0.6× 28 496
Meisi Lin China 7 128 1.0× 35 0.3× 46 0.7× 34 0.6× 38 0.7× 12 388
Elham Abdelmonem Mohamed Egypt 12 139 1.1× 46 0.4× 36 0.5× 22 0.4× 30 0.6× 21 466
Yan-Qiang Huang China 14 144 1.1× 40 0.4× 27 0.4× 80 1.4× 74 1.5× 34 481
Jingnan Xu China 14 157 1.2× 63 0.6× 25 0.4× 73 1.3× 117 2.3× 38 503

Countries citing papers authored by Ankit Tanwar

Since Specialization
Citations

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

Fields of papers citing papers by Ankit Tanwar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ankit Tanwar

This figure shows the co-authorship network connecting the top 25 collaborators of Ankit Tanwar. A scholar is included among the top collaborators of Ankit Tanwar 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 Ankit Tanwar. Ankit Tanwar 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.
Tanwar, Ankit, et al.. (2025). The B7-H3 (CD276) pathway: emerging biology and clinical therapeutics. Trends in Pharmacological Sciences. 46(10). 975–988.
2.
Wang, Hao, R. Alejandro Sica, Gurbakhash Kaur, et al.. (2024). TMIGD2 is an orchestrator and therapeutic target on human acute myeloid leukemia stem cells. Nature Communications. 15(1). 11–11. 32 indexed citations
3.
4.
Lu, Linchao, Shweta Varshney, Youxi Yuan, et al.. (2023). In vivo evidence for GDP-fucose transport in the absence of transporter SLC35C1 and putative transporter SLC35C2. Journal of Biological Chemistry. 299(12). 105406–105406. 6 indexed citations
5.
Madsen, Anne Tranberg, et al.. (2023). Recent advancements in the B7/CD28 immune checkpoint families: new biology and clinical therapeutic strategies. Cellular and Molecular Immunology. 20(7). 694–713. 48 indexed citations
6.
Silva, Zélia, et al.. (2023). Generation of Monocyte-Derived Dendritic Cells with Differing Sialylated Phenotypes. Journal of Visualized Experiments. 1 indexed citations
7.
Tanwar, Ankit & Pamela Stanley. (2023). Synergistic regulation of Notch signaling by different O-glycans promotes hematopoiesis. Frontiers in Immunology. 14. 1097332–1097332. 5 indexed citations
8.
Stanley, Pamela & Ankit Tanwar. (2022). Regulation of myeloid and lymphoid cell development by O-glycans on Notch. Frontiers in Molecular Biosciences. 9. 979724–979724. 10 indexed citations
9.
Tanwar, Ankit, Harvinder Kaur, Raman Chawla, et al.. (2019). In silico bioprospection analysis for identification of herbal compound targeting Clostridium difficile. 18(4). 655–661. 1 indexed citations
10.
Varshney, Shweta, Frank Batista, Subha Sundaram, et al.. (2019). A modifier in the 129S2/SvPasCrl genome is responsible for the viability of Notch1[12f/12f] mice. BMC Developmental Biology. 19(1). 19–19. 15 indexed citations
11.
Tanwar, Ankit, Manish Bhardwaj, Ankita Singh Chakotiya, et al.. (2018). Herbal informatics approach for the selection of natural compounds targeting diabetes mellitus. 2 indexed citations
12.
Tanwar, Ankit, Raman Chawla, Md. Meraj Ansari, et al.. (2017). In vivo anti-arthritic efficacy of Camellia sinensis (L.) in collagen induced arthritis model. Biomedicine & Pharmacotherapy. 87. 92–101. 21 indexed citations
13.
Chakotiya, Ankita Singh, Ankit Tanwar, Alka Narula, & Rakesh Kumar Sharma. (2017). Zingiber officinale : Its antibacterial activity on Pseudomonas aeruginosa and mode of action evaluated by flow cytometry. Microbial Pathogenesis. 107. 254–260. 54 indexed citations
14.
Chakotiya, Ankita Singh, Ankit Tanwar, Pranay Srivastava, Alka Narula, & Rakesh Kumar Sharma. (2017). Effect of aquo-alchoholic extract of Glycyrrhiza glabra against Pseudomonas aeruginosa in Mice Lung Infection Model. Biomedicine & Pharmacotherapy. 90. 171–178. 26 indexed citations
15.
Tanwar, Ankit, Pallavi Thakur, Raman Chawla, et al.. (2017). Curative remedies for rheumatoid arthritis: Herbal informatics approach for rational based selection of natural plant products. 4 indexed citations
16.
Tanwar, Ankit, Raman Chawla, Ankita Singh Chakotiya, et al.. (2016). Effect of Holarrhena antidysentrica (Ha) and Andrographis paniculata (Ap) on the biofilm formation and cell membrane integrity of opportunistic pathogen Salmonella typhimurium. Microbial Pathogenesis. 101. 76–82. 10 indexed citations
17.
Thakur, Pallavi, Raman Chawla, Ankit Tanwar, et al.. (2016). Attenuation of adhesion, quorum sensing and biofilm mediated virulence of carbapenem resistant Escherichia coli by selected natural plant products. Microbial Pathogenesis. 92. 76–85. 39 indexed citations
18.
19.
Chakotiya, Ankita Singh, Raman Chawla, Pallavi Thakur, et al.. (2016). In vitro bactericidal activity of promising nutraceuticals for targeting multidrug resistant Pseudomonas aeruginosa. Nutrition. 32(7-8). 890–897. 21 indexed citations
20.
Thakur, Pallavi, Raman Chawla, Ankita Singh Chakotiya, et al.. (2015). Camellia sinensis Ameliorates the Efficacy of Last Line Antibiotics Against Carbapenem Resistant Escherichia coli. Phytotherapy Research. 30(2). 314–322. 17 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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