Sushil Devkota

3.1k citations
16 papers · 388 · h-index 11

Impact in

  • Aging top 10%
    • Genetics, Aging, and Longevity in Model Organisms
    • Autophagy in Disease and Therapy

Papers in

    • Ubiquitin and proteasome pathways 4
    • CRISPR and Genetic Engineering 3
    • Pluripotent Stem Cells Research 2
    • RNA Interference and Gene Delivery 2
    • Cancer-related Molecular Pathways 3

Sushil Devkota

16 papers receiving 384 citations

Peers

Sushil Devkota
Comparison fields: 5 of 71
  • Aging 29
  • Epidemiology 115
  • Business and International Management 8
  • Cell Biology 58
  • Molecular Biology 223
Replace Vanessa Chenouard with:
Vanessa Chenouard France
Christian Covill‐Cooke United Kingdom
Jon Iker Etchegaray United States
Renuka Prasad South Korea
Clémence Levet United Kingdom
Jonas Zaugg Switzerland
Artem Zykovich United States
Eline C. Brombacher Netherlands
Sarallah Rezazadeh United States
Huiqian Chen China
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Citations per field
00.5×2.9×
Vanessa Chenouard · 1×
Citations per year

Countries citing papers authored by Sushil Devkota

Since Specialization
Citations

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

Fields of papers citing papers by Sushil Devkota

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 201794
2 201854
3 201639
4 201735
5 201629
6 201329
7 201620
8 201217
9 201316
10 201014
11 202112
12 20209
13 20198
14 20165
15 20214
16 20223

About Sushil Devkota

Sushil Devkota is a scholar working on Molecular Biology, Oncology, Epidemiology, Cell Biology and Physiology, having authored 16 papers that have together received 388 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (4 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Cancer-related Molecular Pathways (3 papers), Telomeres, Telomerase, and Senescence (3 papers), Autophagy in Disease and Therapy (3 papers), CRISPR and Genetic Engineering (3 papers), Pluripotent Stem Cells Research (2 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Aging (29 citations), Epidemiology (115 citations), Business and International Management (8 citations), Cell Biology (58 citations) and Molecular Biology (223 citations). Sushil Devkota has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Han‐Woong Lee, Taewook Nam, Young Hoon Sung, Jaehoon Lee, Muhammad Ali, Daehee Hwang, Yunmi Kim, Hoonkyo Suh, Jae‐Hoon Lee and Muhammad Ali. Their work appears in journals such as The International Journal of Biochemistry & Cell Biology, Biochemical and Biophysical Research Communications, Oncogene, Oncotarget and Translational Psychiatry.

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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