Maya Gopalakrishnan

513 citations
43 papers · 326 · h-index 9

Impact in

  • Virology top 5%
    • Rabies epidemiology and control
    • Venomous Animal Envenomation and Studies

Papers in

    • Venomous Animal Envenomation and Studies 16
    • COVID-19 Clinical Research Studies 5
    • Viral Infections and Vectors 4
    • Amoebic Infections and Treatments 2

Maya Gopalakrishnan

39 papers receiving 310 citations

Peers

Maya Gopalakrishnan
Comparison fields: 5 of 75
  • Virology 82
  • Genetics 118
  • Paleontology 26
  • Infectious Diseases 64
  • Neurology 49
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Nishanth Dev India
Luis Idrovo Ecuador
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Citations per year

Countries citing papers authored by Maya Gopalakrishnan

Since Specialization
Citations

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

Fields of papers citing papers by Maya Gopalakrishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Maya Gopalakrishnan, 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 Maya Gopalakrishnan Line = papers co-authored together Maya Gopalakrishnan 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
Effect of six weeks yoga training on weight loss following step test, respiratory pressures, handgrip strength and handgrip endurance in young healthy subjects.
200958
2 202038
3 202127
4 201821
5 202019
6 201518
7 202115
8 202111
9 202111
10 20128
11 20198
12 20228
13 20217
14 20217
15 20126
16 20205
17 20205
18 20045
19 20184
20 20224

About Maya Gopalakrishnan

Maya Gopalakrishnan is a scholar working on Genetics, Infectious Diseases, Virology, Surgery and Public Health, Environmental and Occupational Health, having authored 43 papers that have together received 326 indexed citations. Recurring topics across this work include Venomous Animal Envenomation and Studies (16 papers), Rabies epidemiology and control (13 papers), COVID-19 Clinical Research Studies (5 papers), Viral Infections and Vectors (4 papers), Vector-borne infectious diseases (3 papers), Marine Invertebrate Physiology and Ecology (3 papers), Mosquito-borne diseases and control (3 papers) and Amoebic Infections and Treatments (2 papers). The work is most often cited by research in Virology (82 citations), Genetics (118 citations), Paleontology (26 citations), Infectious Diseases (64 citations) and Neurology (49 citations). Maya Gopalakrishnan has collaborated with scholars based in India, Australia and United Kingdom. Frequent co-authors include Mahendra Kumar Garg, Sanjeev Misra, B Selvakumar, Madanmohan, Suman Saurabh, Tarun Kumar Dutta, Srinivas Rajagopala, Molly Mary Thabah, Naresh Kumar Midha and Soumyadeep Bhaumik. Their work appears in journals such as Transactions of the Royal Society of Tropical Medicine and Hygiene, American Journal of Tropical Medicine and Hygiene, QJM, Endocrine Connections and Journal of the National Medical Association.

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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