Amit Kumar Singh

1.0k citations
43 papers · 669 · h-index 13

Impact in

Papers in

Amit Kumar Singh

41 papers receiving 654 citations

Peers

Amit Kumar Singh
Comparison fields: 5 of 94
  • Computational Theory and Mathematics 275
  • Infectious Diseases 213
  • Molecular Medicine 50
  • Geriatrics and Gerontology 27
  • Pharmacology 42
Replace Dhamodharan Prabhu with:
Dhamodharan Prabhu India
Md. Arif Khan Bangladesh
Kiran Bharat Lokhande India
Arif Ali China
Sivakumar Prasanth Kumar India
Jung Sun Min South Korea
Abdulrahim A. Alzain Sudan
Arli Aditya Parikesit Indonesia
Ikechukwu Achilonu South Africa
Amit Kumar Singh relative to Dhamodharan Prabhu India Dhamodharan Prabhu's profile →
Citations per field
00.5×2×4×6.8×
Dhamodharan Prabhu · 1×
Citations per year

Countries citing papers authored by Amit Kumar Singh

Since Specialization
Citations

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

Fields of papers citing papers by Amit Kumar Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020279
2 202045
3 202239
4 202238
5 202027
6 202021
7 202417
8 201917
9 202015
10 202215
11 202015
12 201915
13 202012
14 202010
15 202110
16 20249
17 20238
18 20228
19 20207
20 20207

About Amit Kumar Singh

Amit Kumar Singh is a scholar working on Molecular Biology, Computational Theory and Mathematics, Molecular Medicine, Infectious Diseases and Nutrition and Dietetics, having authored 43 papers that have together received 669 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (14 papers), Antibiotic Resistance in Bacteria (10 papers), Protein Structure and Dynamics (5 papers), Biochemical and Structural Characterization (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Infant Nutrition and Health (3 papers), Cancer therapeutics and mechanisms (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Computational Theory and Mathematics (275 citations), Infectious Diseases (213 citations), Molecular Medicine (50 citations), Geriatrics and Gerontology (27 citations) and Pharmacology (42 citations). Amit Kumar Singh has collaborated with scholars based in India, Saudi Arabia and Indonesia. Frequent co-authors include Jayaraman Muthukumaran, Monika Jain, Gizachew Muluneh Amera, Rameez Jabeer Khan, Rajat Kumar Jha, Ekampreet Singh, Amita Pathak, Rashmi Prabha Singh, Ankit Kumar and Abhishek Sharma. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Journal of Molecular Modeling, Journal of Molecular Liquids, Journal of Molecular Graphics and Modelling and Molecular Simulation.

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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