Prasanna Kumar

1.1k citations
42 papers · 609 · h-index 12

Impact in

  • Oncology top 10%
    • Cancer-related Molecular Pathways
    • Cancer Immunotherapy and Biomarkers
    • Immune cells in cancer
    • Immune Cell Function and Interaction

Papers in

Prasanna Kumar

40 papers receiving 594 citations

Peers

Prasanna Kumar
Comparison fields: 5 of 71
  • Oncology 218
  • Immunology 152
  • Obstetrics and Gynecology 36
  • Urology 29
  • Hematology 41
Replace José M. Muñoz‐Félix with:
José M. Muñoz‐Félix Spain
Donna Dunn United States
Silvia Ursino Italy
Karim Harhouri France
Kazushi Shigeno Japan
Toshinori Oka Japan
Veronica Mason United States
Arshad A. Pandith India
Prasanna Kumar relative to José M. Muñoz‐Félix Spain José M. Muñoz‐Félix's profile →
Citations per field
00.5×4.8×
José M. Muñoz‐Félix · 1×
Citations per year

Countries citing papers authored by Prasanna Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Prasanna Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Prasanna Kumar, 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 Prasanna Kumar Line = papers co-authored together Prasanna Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016156
2 201768
3 202363
4 200942
5 201839
6 201731
7 201630
8 201526
9 201622
10 201617
11 201817
12 201411
13 202310
14 20189
15 20069
16 20128
17 20155
18
Proteomics of renal disorders: Urinary proteome analysis by two-dimensional gel electrophoresis and MALDI-TOF mass spectrometry
20024
19 20224
20 20194

About Prasanna Kumar

Prasanna Kumar is a scholar working on Oncology, Molecular Biology, Hematology, Pulmonary and Respiratory Medicine and Endocrinology, Diabetes and Metabolism, having authored 42 papers that have together received 609 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (7 papers), Cancer-related Molecular Pathways (5 papers), Cancer Genomics and Diagnostics (4 papers), Immune cells in cancer (3 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers), Gastrointestinal Tumor Research and Treatment (2 papers), Virus-based gene therapy research (2 papers) and Diabetes Management and Research (2 papers). The work is most often cited by research in Oncology (218 citations), Immunology (152 citations), Obstetrics and Gynecology (36 citations), Urology (29 citations) and Hematology (41 citations). Prasanna Kumar has collaborated with scholars based in United States, India and Japan. Frequent co-authors include Andres Forero, Johanna C. Bendell, Sridevi Mony, Fang Wang, Robert L. Witt, Thomas Condamine, Qin Liu, Ayumi Hashimoto, George A. Dominguez and Neil Hockstein. Their work appears in journals such as Blood, Journal of Clinical Oncology, Clinical Cancer Research, Molecular Therapy and Molecular Cancer Therapeutics.

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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