Babita Agrawal

2.4k total citations
65 papers, 1.9k citations indexed

About

Babita Agrawal is a scholar working on Immunology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Babita Agrawal has authored 65 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Immunology, 23 papers in Infectious Diseases and 23 papers in Epidemiology. Recurrent topics in Babita Agrawal's work include Hepatitis C virus research (23 papers), Immunotherapy and Immune Responses (18 papers) and Hepatitis B Virus Studies (16 papers). Babita Agrawal is often cited by papers focused on Hepatitis C virus research (23 papers), Immunotherapy and Immune Responses (18 papers) and Hepatitis B Virus Studies (16 papers). Babita Agrawal collaborates with scholars based in Canada, United States and Austria. Babita Agrawal's co-authors include B. Michael Longenecker, Mark J. Krantz, Rakesh Kumar, Mark A. Reddish, Joanne L. Parker, Sandra Gendler, D. Lorne Tyrrell, Nancy Gupta, Dennis Kunimoto and Deepa Kolaseri Krishnadas and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Babita Agrawal

63 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Babita Agrawal Canada 26 865 848 339 324 300 65 1.9k
Mark Kowalski United States 21 991 1.1× 829 1.0× 349 1.0× 322 1.0× 876 2.9× 50 2.8k
Thomas Powell United States 16 1.1k 1.2× 753 0.9× 521 1.5× 160 0.5× 249 0.8× 31 2.4k
Carol Silverman United States 20 1.6k 1.9× 1.1k 1.3× 426 1.3× 169 0.5× 155 0.5× 27 2.8k
Margaret Goodall United Kingdom 31 1.3k 1.5× 1.7k 2.0× 334 1.0× 1.2k 3.6× 413 1.4× 76 3.6k
Mike Westby United Kingdom 22 824 1.0× 809 1.0× 552 1.6× 178 0.5× 1.5k 4.9× 46 3.0k
Nazzareno Dimasi United States 25 910 1.1× 989 1.2× 187 0.6× 933 2.9× 115 0.4× 62 2.6k
Tony S. Mondala United States 19 1.1k 1.3× 424 0.5× 316 0.9× 232 0.7× 71 0.2× 26 2.0k
Stefania Capone Italy 29 650 0.8× 581 0.7× 854 2.5× 136 0.4× 396 1.3× 77 2.3k
Franco M. Buonaguro Italy 34 1.3k 1.5× 732 0.9× 1.2k 3.5× 285 0.9× 202 0.7× 111 3.4k
Gregory A. Viglianti United States 24 813 0.9× 1.9k 2.2× 337 1.0× 145 0.4× 287 1.0× 42 3.0k

Countries citing papers authored by Babita Agrawal

Since Specialization
Citations

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

Fields of papers citing papers by Babita Agrawal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Babita Agrawal

This figure shows the co-authorship network connecting the top 25 collaborators of Babita Agrawal. A scholar is included among the top collaborators of Babita Agrawal 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 Babita Agrawal. Babita Agrawal 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.
Bavananthasivam, Jegarubee, Melissa Hewitt, Jagdeep K. Sandhu, et al.. (2025). Mixed lipopeptide-based mucosal vaccine candidate induces cross-variant immunity and protects against SARS-CoV-2 infection in hamsters. ImmunoHorizons. 9(2). 1 indexed citations
2.
3.
Agrawal, Babita, et al.. (2022). Heterologous immunity induced by 1st generation COVID-19 vaccines and its role in developing a pan-coronavirus vaccine. Frontiers in Immunology. 13. 952229–952229. 9 indexed citations
4.
5.
Agrawal, Babita, Nancy Gupta, & Jeffrey D. Konowalchuk. (2018). MUC1 Mucin: A Putative Regulatory (Checkpoint) Molecule of T Cells. Frontiers in Immunology. 9. 2391–2391. 27 indexed citations
6.
Agrawal, Babita, et al.. (2017). Unsolved Puzzles Surrounding HCV Immunity: Heterologous Immunity Adds Another Dimension. International Journal of Molecular Sciences. 18(8). 1626–1626. 9 indexed citations
7.
8.
Agrawal, Amogh, Subodh Kumar Samrat, Babita Agrawal, D. Lorne Tyrrell, & Rakesh Kumar. (2014). Co-Incubation with Core Proteins of HBV and HCV Leads to Modulation of Human Dendritic Cells. Viral Immunology. 27(8). 412–417. 6 indexed citations
9.
Samrat, Subodh Kumar, Wen Li, Shakti Singh, Rakesh Kumar, & Babita Agrawal. (2014). Alternate Reading Frame Protein (F Protein) of Hepatitis C Virus: Paradoxical Effects of Activation and Apoptosis on Human Dendritic Cells Lead to Stimulation of T Cells. PLoS ONE. 9(1). e86567–e86567. 15 indexed citations
10.
Konowalchuk, Jeffrey D. & Babita Agrawal. (2011). MUC1 mucin is expressed on human T-regulatory cells: Function in both co-stimulation and co-inhibition. Cellular Immunology. 272(2). 193–199. 14 indexed citations
11.
Vivithanaporn, Pornpun, Ferdinand Maingat, Liang Lin, et al.. (2010). Hepatitis C Virus Core Protein Induces Neuroimmune Activation and Potentiates Human Immunodeficiency Virus-1 Neurotoxicity. PLoS ONE. 5(9). e12856–e12856. 64 indexed citations
12.
13.
Krishnadas, Deepa Kolaseri, Wen Li, Rakesh Kumar, D. Lorne Tyrrell, & Babita Agrawal. (2009). HCV-core and NS3 antigens play disparate role in inducing regulatory or effector T cells in vivo: Implications for viral persistence or clearance. Vaccine. 28(9). 2104–2114. 20 indexed citations
14.
Wen, Li, Deepa Kolaseri Krishnadas, Jie Li, D. Lorne Tyrrell, & Babita Agrawal. (2006). Induction of Primary Human T Cell Responses against Hepatitis C Virus-Derived Antigens NS3 or Core by Autologous Dendritic Cells Expressing Hepatitis C Virus Antigens: Potential for Vaccine and Immunotherapy. The Journal of Immunology. 176(10). 6065–6075. 39 indexed citations
15.
Mukherjee, Pinku, Cathy S. Madsen, Teresa L. Tinder, et al.. (2003). Mucin 1-specific immunotherapy in a mouse model of spontaneous breast cancer.. Journal of Immunotherapy. 26(1). 47–62. 72 indexed citations
16.
Agrawal, Babita, et al.. (2000). A Self MHC Class II β-Chain Peptide Prevents Diabetes in Nonobese Diabetic Mice. The Journal of Immunology. 164(12). 6610–6620. 17 indexed citations
17.
Agrawal, Babita, Mark J. Krantz, Mark A. Reddish, & B. Michael Longenecker. (1998). Cancer-associated MUC1 mucin inhibits human T-cell proliferation, which is reversible by IL-2. Nature Medicine. 4(1). 43–49. 252 indexed citations
18.
Agrawal, Babita, Mark J. Krantz, Joanne L. Parker, & B. Michael Longenecker. (1998). Expression of MUC1 mucin on activated human T cells: implications for a role of MUC1 in normal immune regulation.. PubMed. 58(18). 4079–81. 131 indexed citations
19.
Agrawal, Babita, Mark A. Reddish, & B. Michael Longenecker. (1996). In vitro induction of MUC-1 peptide-specific type 1 T lymphocyte and cytotoxic T lymphocyte responses from healthy multiparous donors. The Journal of Immunology. 157(5). 2089–2095. 56 indexed citations
20.
Agrawal, Babita, Ester Fraga, Kevin P. Kane, & Bhagirath Singh. (1994). Up-regulation of the MHC class II molecules on B cells by peptide ligands.. The Journal of Immunology. 152(3). 965–975. 7 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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