Saroj Kumar Panda

557 citations
29 papers · 426 · h-index 13

Impact in

Papers in

    • vaccines and immunoinformatics approaches 7
    • Cancer therapeutics and mechanisms 3
    • SARS-CoV-2 and COVID-19 Research 7
    • Parasitic Diseases Research and Treatment 3

Saroj Kumar Panda

26 papers receiving 424 citations

Peers

Saroj Kumar Panda
Comparison fields: 5 of 71
  • Infectious Diseases 145
  • Virology 28
  • Computational Theory and Mathematics 84
  • Parasitology 24
  • Molecular Biology 225
Replace Dhaneswar Prusty with:
Dhaneswar Prusty India
Matthew B. Huante United States
Rupal Ojha India
Philipp P. Henrich United States
Ganesh Chandra Sahoo India
Zhenghui Huang China
Marı́a Belén Jiménez-Dı́az Spain
Louis J. Nkrumah United States
Jérôme Clain France
Muhammad Shahab China
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Citations per field
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Citations per year

Countries citing papers authored by Saroj Kumar Panda

Since Specialization
Citations

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

Fields of papers citing papers by Saroj Kumar Panda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202244
2 202043
3 202142
4 202240
5 201938
6 202334
7 202129
8 202325
9 202221
10 202214
11 202114
12 202413
13 202113
14 20239
15 20239
16 20219
17 20235
18 20235
19 20234
20 20244

About Saroj Kumar Panda

Saroj Kumar Panda is a scholar working on Molecular Biology, Infectious Diseases, Computational Theory and Mathematics, Organic Chemistry and Virology, having authored 29 papers that have together received 426 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), SARS-CoV-2 and COVID-19 Research (7 papers), vaccines and immunoinformatics approaches (7 papers), Click Chemistry and Applications (3 papers), Antibiotic Resistance in Bacteria (3 papers), Synthesis and biological activity (3 papers), Cancer therapeutics and mechanisms (3 papers) and Parasitic Diseases Research and Treatment (3 papers). The work is most often cited by research in Infectious Diseases (145 citations), Virology (28 citations), Computational Theory and Mathematics (84 citations), Parasitology (24 citations) and Molecular Biology (225 citations). Saroj Kumar Panda has collaborated with scholars based in India, United States and Austria. Frequent co-authors include Malay Kumar Rana, Parth Sarthi Sen Gupta, Suprabhat Mukherjee, Shalini Saxena, Nabarun Chandra Das, Lalitha Guruprasad, Abhigyan Choudhury, Ritwik Patra, Nisheeth C. Desai and Bhaskaran Shankar. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, International Immunopharmacology, The Journal of Physical Chemistry Letters, Journal of Molecular Liquids and ACS Infectious 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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