Sunil Laxman

2.2k citations
58 papers · 1.5k · h-index 23

Impact in

Papers in

    • Fungal and yeast genetics research 12
    • Polyamine Metabolism and Applications 9
    • Mitochondrial Function and Pathology 7
    • RNA modifications and cancer 7
    • ATP Synthase and ATPases Research 5
    • Biochemical and Molecular Research 5
    • RNA and protein synthesis mechanisms 5
    • Microbial Metabolic Engineering and Bioproduction 5

Sunil Laxman

55 papers receiving 1.5k citations

Peers

Sunil Laxman
Comparison fields: 5 of 102
  • Aging 82
  • Biochemistry 115
  • Molecular Biology 1.1k
  • Epidemiology 271
  • Geriatrics and Gerontology 26
Replace H. Gut with:
H. Gut Switzerland
Guillaume Thibault Singapore
Marek Skoneczny Poland
Helmut Jungwirth Austria
Bertrand Daignan‐Fornier France
Cheol‐Sang Hwang South Korea
Amere Subbarao Sreedhar India
Maria A. Bauer Austria
Dylan J. Sorensen United States
Joanna Rytka Poland
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Citations per field
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Citations per year

Countries citing papers authored by Sunil Laxman

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Laxman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013201
2 2013191
3 200675
4 201666
5 201664
6 201961
7 201356
8 201345
9 200740
10 201538
11 201437
12 201936
13 201536
14 201935
15 202135
16 201834
17 200533
18 201930
19 200427
20 201925

About Sunil Laxman

Sunil Laxman is a scholar working on Molecular Biology, Epidemiology, Cell Biology, Biochemistry and Plant Science, having authored 58 papers that have together received 1.5k indexed citations. Recurring topics across this work include Fungal and yeast genetics research (12 papers), Polyamine Metabolism and Applications (9 papers), Mitochondrial Function and Pathology (7 papers), RNA modifications and cancer (7 papers), ATP Synthase and ATPases Research (5 papers), Biochemical and Molecular Research (5 papers), RNA and protein synthesis mechanisms (5 papers) and Microbial Metabolic Engineering and Bioproduction (5 papers). The work is most often cited by research in Aging (82 citations), Biochemistry (115 citations), Molecular Biology (1.1k citations), Epidemiology (271 citations) and Geriatrics and Gerontology (26 citations). Sunil Laxman has collaborated with scholars based in India, United States and Venezuela. Frequent co-authors include Benjamin P. Tu, Benjamin M. Sutter, Xi Wu, Joseph A. Beavo, Adhish S. Walvekar, Xiaofeng Guo, David C. Trudgian, Sujai Kumar, Hamid Mirzaei and Jyotsna Dhawan. Their work appears in journals such as eLife, Journal of Biological Chemistry, Proceedings of the National Academy of Sciences, Science Advances and Nature Communications.

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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