Prasanna Kumar

1.1k citations
42 papers · 582 · h-index 12

Impact in

  • Oncology top 10%
    • Cancer-related Molecular Pathways
    • Cancer Immunotherapy and Biomarkers
  • Urology top 10%
    • Urological Disorders and Treatments

Papers in

Prasanna Kumar

39 papers receiving 567 citations

Peers

Prasanna Kumar
Comparison fields: 5 of 74
  • Oncology 244
  • Urology 52
  • Immunology 152
  • Obstetrics and Gynecology 47
  • Hematology 45
Replace M. Bianchi with:
M. Bianchi Italy
Fumihiro Kimura Japan
Piero De Carli Italy
Kazushi Shigeno Japan
Masafumi Inokuchi Japan
Tatsuaki Yoneda Japan
Teruaki Kumazawa Japan
Ming Y. Tung United States
G Delides Greece
Prasanna Kumar relative to M. Bianchi Italy M. Bianchi's profile →
Citations per field
00.5×3.8×
M. Bianchi · 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 2016152
2 201762
3 202356
4 200942
5 201836
6 201730
7 201629
8 201526
9 201622
10 201617
11 201816
12 201411
13 20239
14 20069
15 20189
16 20128
17
Proteomics of renal disorders: Urinary proteome analysis by two-dimensional gel electrophoresis and MALDI-TOF mass spectrometry
20024
18 20154
19 20224
20
Effect of D-400 on Blood Glucose Profile in Non-Insulin Dependent Diabetes Mellitus Patients
19954

About Prasanna Kumar

Prasanna Kumar is a scholar working on Molecular Biology, Oncology, Surgery, Pulmonary and Respiratory Medicine and Hematology, having authored 42 papers that have together received 582 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (7 papers), Cancer Genomics and Diagnostics (6 papers), Cancer-related Molecular Pathways (5 papers), Protein Degradation and Inhibitors (3 papers), Diabetes and associated disorders (3 papers), Immune cells in cancer (3 papers), Diabetes Management and Research (2 papers) and Virus-based gene therapy research (2 papers). The work is most often cited by research in Oncology (244 citations), Urology (52 citations), Immunology (152 citations), Obstetrics and Gynecology (47 citations) and Hematology (45 citations). Prasanna Kumar has collaborated with scholars based in United States, India and Japan. Frequent co-authors include Andres Forero, Johanna C. Bendell, George A. Dominguez, Dmitry I. Gabrilovich, Neil Hockstein, Ayumi Hashimoto, Sridevi Mony, Qin Liu, Fang Wang and Robert L. Witt. Their work appears in journals such as Journal of Clinical Oncology, Blood, 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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