Padma P. Nanaware

455 total citations
18 papers, 243 citations indexed

About

Padma P. Nanaware is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Padma P. Nanaware has authored 18 papers receiving a total of 243 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Immunology and 4 papers in Genetics. Recurrent topics in Padma P. Nanaware's work include Immunotherapy and Immune Responses (7 papers), vaccines and immunoinformatics approaches (6 papers) and T-cell and B-cell Immunology (4 papers). Padma P. Nanaware is often cited by papers focused on Immunotherapy and Immune Responses (7 papers), vaccines and immunoinformatics approaches (6 papers) and T-cell and B-cell Immunology (4 papers). Padma P. Nanaware collaborates with scholars based in United States, India and Israel. Padma P. Nanaware's co-authors include Lawrence J. Stern, Prasanna Venkatraman, Mollie Jurewicz, Arun Kumar Somavarapu, Scott A. Shaffer, Nafisa Balasinor, Zuping He, Ryan S. D’Souza, John Leszyk and Susan Idicula‐Thomas and has published in prestigious journals such as Immunity, The Journal of Immunology and FEBS Letters.

In The Last Decade

Padma P. Nanaware

17 papers receiving 242 citations

Peers

Padma P. Nanaware

IMMUN

GENET

Adam R. Lefferts United States

Joris van Montfrans Netherlands

Wenjing Tang China

Anja Honegger Germany

Oliver Dietrich Germany

Qian‐Ying Zhu China

Ming-quan Su China

Yuri Ishizu Japan

Michael S. O’Keeffe United States

Rena Levin-Klein Israel

Adam R. Lefferts United States

Padma P. Nanaware

138 ×1.3

IMMUN

89 ×0.9

38 ×0.9

GENET

21 ×0.6

12 ×0.4

Citations per year, relative to Padma P. Nanaware Padma P. Nanaware (= 1×) peers Adam R. Lefferts

Countries citing papers authored by Padma P. Nanaware

Since Specialization

Citations

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

Fields of papers citing papers by Padma P. Nanaware

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Padma P. Nanaware. 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 Padma P. Nanaware. The network helps show where Padma P. Nanaware may publish in the future.

Co-authorship network of co-authors of Padma P. Nanaware

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

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Nanaware, Padma P., J. Mauricio Calvo‐Calle, Sambra D. Redick, et al.. (2025). The antigen presentation landscape of cytokine-stressed human pancreatic islets. Cell Reports. 44(8). 115927–115927.

Santambrogio, Laura, Cristina C. Clement, Aniuska Becerra, et al.. (2024). Molecular Mimicry in Pathogen Immune Evasion. The Journal of Immunology. 212(1_Supplement). 1438_4569–1438_4569. 1 indexed citations

Jones, Michael C., Padma P. Nanaware, Brian D. Stadinski, et al.. (2023). CD4 Effector TCR Avidity for Peptide on APC Determines the Level of Memory Generated. The Journal of Immunology. 210(12). 1950–1961. 6 indexed citations

Nanaware, Padma P., John Cruz, Khaja Muneeruddin, Scott A. Shaffer, & Lawrence J. Stern. (2023). Inhibited MHC Class I and MHC Class II antigen processing and presentation upon Sars-CoV-2 infection. The Journal of Immunology. 210(Supplement_1). 222.02–222.02. 1 indexed citations

Nanaware, Padma P., et al.. (2023). Immunopeptidome profiling of human coronavirus OC43-infected cells identifies CD4 T-cell epitopes specific to seasonal coronaviruses or cross-reactive with SARS-CoV-2. PLoS Pathogens. 19(7). e1011032–e1011032. 10 indexed citations

Calvo‐Calle, J. Mauricio, Padma P. Nanaware, John Cruz, et al.. (2022). Broadly recognized, cross-reactive SARS-CoV-2 CD4 T cell epitopes are highly conserved across human coronaviruses and presented by common HLA alleles. Cell Reports. 39(11). 110952–110952. 18 indexed citations

Jurewicz, Mollie, Padma P. Nanaware, & Lawrence J. Stern. (2022). MHC class II peptide loading regulates selection and function of regulatory T cells. Molecular Immunology. 150. 3–3. 3 indexed citations

Ghosh, Debopam, Tho D. Pham, Padma P. Nanaware, et al.. (2022). Regulation of the BCR signalosome by the class II peptide editor, H2-M, affects the development and repertoire of innate-like B cells. Cell Reports. 38(4). 110200–110200. 3 indexed citations

Nanaware, Padma P., Mollie Jurewicz, Cristina C. Clement, et al.. (2021). Distinguishing Signal From Noise in Immunopeptidome Studies of Limiting-Abundance Biological Samples: Peptides Presented by I-Ab in C57BL/6 Mouse Thymus. Frontiers in Immunology. 12. 658601–658601. 10 indexed citations

10.

Clement, Cristina C., Padma P. Nanaware, Takahiro Yamazaki, et al.. (2021). Pleiotropic consequences of metabolic stress for the major histocompatibility complex class II molecule antigen processing and presentation machinery. Immunity. 54(4). 721–736.e10. 36 indexed citations

11.

Clement, Cristina C., Padma P. Nanaware, Lawrence J. Stern, & Laura Santambrogio. (2021). A protocol for qualitative and quantitative measurement of endosomal processing using hot spot analysis. STAR Protocols. 2(3). 100648–100648. 2 indexed citations

12.

Chikhale, Rupesh V., et al.. (2021). A druggable pocket on PSMD10Gankyrin that can accommodate an interface peptide and doxorubicin. European Journal of Pharmacology. 915. 174718–174718. 6 indexed citations

13.

Refat, Maggi Ahmed, et al.. (2020). Current Insights in Cutaneous Lupus Erythematosus Immunopathogenesis. Frontiers in Immunology. 11. 1353–1353. 29 indexed citations

14.

Sahu, Indrajit, et al.. (2019). Role of a 19S Proteasome Subunit- PSMD10^Gankyrin in Neurogenesis of Human Neural Progenitor Cells. International Journal of Stem Cells. 12(3). 463–473. 4 indexed citations

15.

Nanaware, Padma P., Mollie Jurewicz, John Leszyk, Scott A. Shaffer, & Lawrence J. Stern. (2018). HLA-DO Modulates the Diversity of the MHC-II Self-peptidome. Molecular & Cellular Proteomics. 18(3). 490–503. 30 indexed citations

16.

Somavarapu, Arun Kumar, et al.. (2013). Identification of a novel ATPase activity in 14‐3‐3 proteins – Evidence from enzyme kinetics, structure guided modeling and mutagenesis studies. FEBS Letters. 588(1). 71–78. 12 indexed citations

17.

Nanaware, Padma P., et al.. (2013). Discovery of multiple interacting partners of gankyrin, a proteasomal chaperone and an oncoprotein—Evidence for a common hot spot site at the interface and its functional relevance. Proteins Structure Function and Bioinformatics. 82(7). 1283–1300. 31 indexed citations

18.

Balasinor, Nafisa, Ryan S. D’Souza, Padma P. Nanaware, et al.. (2010). Effect of high intratesticular estrogen on global gene expression and testicular cell number in rats. Reproductive Biology and Endocrinology. 8(1). 72–72. 41 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.

Explore authors with similar magnitude of impact