Richard Mariadasse

412 citations
17 papers · 299 indexed · h-index 10
Topics
Computational Drug Discovery Methods (6 papers)SARS-CoV-2 and COVID-19 Research (4 papers)Molecular Sensors and Ion Detection (3 papers)
Partner nations
IndiaUnited StatesFrance

In The Last Decade

Richard Mariadasse

17 papers receiving 294 citations

Peers

Richard Mariadasse
Comparison fields: 5 of 66
  • Molecular Biology 117
  • Spectroscopy 108
  • Materials Chemistry 92
  • Computational Theory and Mathematics 59
  • Infectious Diseases 54
Replace Hyung‐Jung Pyun with:
Hyung‐Jung Pyun United States
Xinjie Guo China
Zhen Liang China
Hakan Kandemir Türkiye
Kung-Tien Liu Taiwan
Yiyong Yan China
Georgi M. Dobrikov Bulgaria
Sevgi Karakuş Türkiye
Matthew W. Freyer United States
Branimir Bertoša Croatia
Richard Mariadasse relative to Hyung‐Jung Pyun United States Hyung‐Jung Pyun's profile →
Citations per field
00.5×5.9×
Hyung‐Jung Pyun · 1×
Citations per year

Countries citing papers authored by Richard Mariadasse

Since Specialization
Citations

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

Fields of papers citing papers by Richard Mariadasse

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Mariadasse

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Mariadasse. A scholar is included among the top collaborators of Richard Mariadasse 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 Richard Mariadasse. Richard Mariadasse is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 1
2 4
3 4
4 20
5 3
6 9
7 3
8 26
9 7
10 10
11 9
12 68
13 23
14 64
15 17
16 15
17 16

About Richard Mariadasse

Richard Mariadasse is a scholar working on Computational Theory and Mathematics, Infectious Diseases and Virology, having authored 17 papers that have together received 299 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), SARS-CoV-2 and COVID-19 Research (4 papers) and Molecular Sensors and Ion Detection (3 papers). The work is most often cited by research in Spectroscopy (108 citations), Bioengineering (33 citations) and Electrochemistry (27 citations). Richard Mariadasse has collaborated with scholars based in India, United States and France. Frequent co-authors include Jeyaraman Jeyakanthan, Munisamy Maniyazagan, Stalin Thambusamy, P. Manisankar, Perumal Muthuraja, S. Naveen, N.K. Lokanath, Mutharasappan Nachiappan, Kumpati Premkumar and Gandhi Sivaraman. Their work appears in journals such as Frontiers in Microbiology, Gene and Sensors and Actuators B Chemical.

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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