Vikas Kumar

61 papers receiving 829 citations

Peers

Vikas Kumar
Comparison fields: 5 of 131
  • Health Informatics 65
  • Computational Theory and Mathematics 166
  • Pharmacology 45
  • Statistics, Probability and Uncertainty 31
  • Surgery 183
Replace Željko Debeljak with:
Željko Debeljak Croatia
David Allen United States
Thomas R. Lane United States
Leihong Wu United States
Josch K. Pauling Germany
Haleema Sadia Pakistan
Alexander Janßen Netherlands
Emmanuelle Voisin France
Kit‐Kay Mak Malaysia
Ana C. Puhl United States
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Citations per field
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Željko Debeljak · 1×
Citations per year

Countries citing papers authored by Vikas Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Vikas Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202065
2 202060
3 202159
4 202149
5 201545
6 201538
7 202235
8 201534
9 202131
10 202029
11 202128
12 202124
13 202121
14 202120
15 202218
16 202217
17 202017
18 202216
19 202115
20 202115

About Vikas Kumar

Vikas Kumar is a scholar working on Molecular Biology, Computational Theory and Mathematics, Surgery, Infectious Diseases and Organic Chemistry, having authored 65 papers that have together received 845 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), Enzyme function and inhibition (7 papers), Shoulder Injury and Treatment (6 papers), PI3K/AKT/mTOR signaling in cancer (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Shoulder and Clavicle Injuries (3 papers) and Reproductive Biology and Fertility (3 papers). The work is most often cited by research in Health Informatics (65 citations), Computational Theory and Mathematics (166 citations), Pharmacology (45 citations), Statistics, Probability and Uncertainty (31 citations) and Surgery (183 citations). Vikas Kumar has collaborated with scholars based in South Korea, India and United States. Frequent co-authors include Keun Woo Lee, Shraddha Parate, Swapandeep Singh Chimni, Gihwan Lee, Ankur Teredesai, Christopher Roche, Howard Routman, Jong Chan Hong, Thomas W. Wright and Joseph D. Zuckerman. Their work appears in journals such as International Journal of Molecular Sciences, Pharmaceuticals, International Journal of Biological Macromolecules, Computers in Biology and Medicine and Journal of Shoulder and Elbow Surgery.

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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