Satya N.V. Arjunan

569 citations
18 papers · 368 indexed · h-index 8
Topics
Gene Regulatory Network Analysis (11 papers)Receptor Mechanisms and Signaling (4 papers)Machine Learning in Bioinformatics (3 papers)
Partner nations
JapanMalaysiaAustralia

In The Last Decade

Satya N.V. Arjunan

18 papers receiving 357 citations

Peers

Satya N.V. Arjunan
Comparison fields: 5 of 70
  • Molecular Biology 291
  • Biophysics 62
  • Genetics 58
  • Computational Theory and Mathematics 38
  • Biomedical Engineering 37
Replace Kazunari Kaizu with:
Kazunari Kaizu Japan
Michael Klann Switzerland
Keegan Hines United States
Mohammad Soltani United States
Yuichi Togashi Japan
Stefan Hellander Sweden
David D. van Niekerk South Africa
Dan T. Gillespie United States
Gabriele Lillacci United States
Satya N.V. Arjunan relative to Kazunari Kaizu Japan Kazunari Kaizu's profile →
Citations per field
00.5×1.5×
Kazunari Kaizu · 1×
Citations per year

Countries citing papers authored by Satya N.V. Arjunan

Since Specialization
Citations

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

Fields of papers citing papers by Satya N.V. Arjunan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Satya N.V. Arjunan. 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 Satya N.V. Arjunan. The network helps show where Satya N.V. Arjunan may publish in the future.

Co-authorship network of co-authors of Satya N.V. Arjunan

This figure shows the co-authorship network connecting the top 25 collaborators of Satya N.V. Arjunan. A scholar is included among the top collaborators of Satya N.V. Arjunan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Satya N.V. Arjunan. Satya N.V. Arjunan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 7
2 4
3 3
4 3
5 11
6 8
7 6
8 9
9 26
10 29
11 1
12 4
13 1
14 12
15 60
16 6
17 176
18
Protein secondary structure prediction from amino acid sequence using artificial intelligence technique
2

About Satya N.V. Arjunan

Satya N.V. Arjunan is a scholar working on Biophysics, Molecular Biology and Computational Theory and Mathematics, having authored 18 papers that have together received 368 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (11 papers), Receptor Mechanisms and Signaling (4 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Biophysics (62 citations), Structural Biology (7 citations) and Molecular Biology (291 citations). Satya N.V. Arjunan has collaborated with scholars based in Japan, Malaysia and Australia. Frequent co-authors include Masaru Tomita, Kouichi Takahashi, Koichi Takahashi, Safaai Deris, Afnizanfaizal Abdullah, Sohail Anwar, Masaki Watabe, Kazunari Kaizu, Kazunari Iwamoto and S. V. Muniandy. Their work appears in journals such as PLoS ONE, FEBS Letters and BMC Bioinformatics.

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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