Pramod Terse

840 citations
33 papers · 683 · h-index 13

Impact in

  • Hematology top 10%
    • Acute Myeloid Leukemia Research
    • Hemoglobinopathies and Related Disorders
    • Virus-based gene therapy research

Papers in

    • Drug-Induced Hepatotoxicity and Protection 4
    • Pharmacogenetics and Drug Metabolism 2
    • Viral Infectious Diseases and Gene Expression in Insects 2
    • CRISPR and Genetic Engineering 2

Pramod Terse

32 papers receiving 665 citations

Peers

Pramod Terse
Comparison fields: 5 of 89
  • Hematology 108
  • Genetics 74
  • Developmental Neuroscience 17
  • Molecular Biology 267
  • Physiology 86
Replace Kazuhiko Matsuno with:
Kazuhiko Matsuno Japan
Eve M. Taylor United States
Osamu Sakai Japan
Huihui Ma China
Hiroyuki Kanoh Japan
Helen H. Lin United States
Gary L. Brodsky United States
Mareike Schulz Germany
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Citations per field
00.5×2×4×6×7.7×
Kazuhiko Matsuno · 1×
Citations per year

Countries citing papers authored by Pramod Terse

Since Specialization
Citations

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

Fields of papers citing papers by Pramod Terse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013120
2 2014107
3 201180
4 201755
5 202044
6 201640
7 202029
8 201924
9 199323
10 201622
11 202221
12 199014
13 201414
14 201811
15 199010
16 20179
17 19908
18 20208
19 20207
20 20206

About Pramod Terse

Pramod Terse is a scholar working on Pharmacology, Molecular Biology, Pharmacology, Genetics and Physiology, having authored 33 papers that have together received 683 indexed citations. Recurring topics across this work include Drug-Induced Hepatotoxicity and Protection (4 papers), Virus-based gene therapy research (4 papers), Muscle metabolism and nutrition (3 papers), CAR-T cell therapy research (2 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Epilepsy research and treatment (2 papers), Pharmacogenetics and Drug Metabolism (2 papers) and CRISPR and Genetic Engineering (2 papers). The work is most often cited by research in Hematology (108 citations), Genetics (74 citations), Developmental Neuroscience (17 citations), Molecular Biology (267 citations) and Physiology (86 citations). Pramod Terse has collaborated with scholars based in United States, New Zealand and Canada. Frequent co-authors include Yonghua Ling, Kenneth K. Chan, Yogen Saunthararajah, Joseph M. Covey, Kory J. Engelke, Reda Z. Mahfouz, R. R. Dalvi, Ali Tabarroki, Quteba Ebrahem and Tomas Radivoyevitch. Their work appears in journals such as Regulatory Toxicology and Pharmacology, Human Gene Therapy, Toxicology and Applied Pharmacology, Journal of Pharmacy and Pharmacology and Avian Diseases.

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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