Nandakumar Packiriswamy

666 citations
31 papers · 446 · h-index 12

Impact in

Papers in

    • Immune Response and Inflammation 6
    • interferon and immune responses 2
    • Virus-based gene therapy research 10

Nandakumar Packiriswamy

29 papers receiving 439 citations

Peers

Nandakumar Packiriswamy
Comparison fields: 5 of 82
  • Agronomy and Crop Science 53
  • Genetics 103
  • Oncology 92
  • Immunology 72
  • Animal Science and Zoology 33
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Citations per field
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Citations per year

Countries citing papers authored by Nandakumar Packiriswamy

Since Specialization
Citations

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

Fields of papers citing papers by Nandakumar Packiriswamy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nandakumar Packiriswamy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nandakumar Packiriswamy Line = papers co-authored together Nandakumar Packiriswamy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202082
2 201570
3 201046
4 201536
5 201325
6 201623
7 201723
8 201718
9 201718
10 201414
11
Role of myeloid-specific G-protein coupled receptor kinase-2 in sepsis.
201114
12
Molecular characterization and computational analysis of the major outer membrane protein (ompH) gene of Pasteurella multocida P52.
201111
13 201710
14 20118
15 20227
16 20167
17 20176
18 20215
19 20195
20 20174

About Nandakumar Packiriswamy

Nandakumar Packiriswamy is a scholar working on Immunology, Genetics, Molecular Biology, Oncology and Infectious Diseases, having authored 31 papers that have together received 446 indexed citations. Recurring topics across this work include Virus-based gene therapy research (10 papers), Immune Response and Inflammation (6 papers), Receptor Mechanisms and Signaling (5 papers), CAR-T cell therapy research (5 papers), NF-κB Signaling Pathways (3 papers), Urological Disorders and Treatments (2 papers), interferon and immune responses (2 papers) and Protein Kinase Regulation and GTPase Signaling (2 papers). The work is most often cited by research in Agronomy and Crop Science (53 citations), Genetics (103 citations), Oncology (92 citations), Immunology (72 citations) and Animal Science and Zoology (33 citations). Nandakumar Packiriswamy has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Lorraine M. Sordillo, Narayanan Parameswaran, Valerie E. Ryman, Stephen J. Russell, Kah-Whye Peng, Angela Dispenzieri, Deepak Upreti, Yumei Zhou, Rehan Khan and Amber Miller. Their work appears in journals such as Journal of Clinical Oncology, Blood, Cancer Research, Genes and Immunity and Cellular Immunology.

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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