S. Anusuya
- Molecular Biology
- Materials Chemistry
- Computational Theory and Mathematics top 5%
- Infectious Diseases
- Plant Science
- Co-authors
- M. Michael GromihaV. AnbazhaganJeyakumar NatarajanDevadasan VelmuruganNisha MuralidharanC. V. RamakrishnanSuresh K. RayalaRamasamy Sakthivel
- Topics
- Computational Drug Discovery Methods (8 papers)Leprosy Research and Treatment (4 papers)Nanoparticles: synthesis and applications (4 papers)
- Cited by
- Computational Theory and MathematicsInfectious DiseasesComplementary and alternative medicine
In The Last Decade
S. Anusuya
34 papers receiving 387 citations
Peers
Comparison fields: 5 of 96
- Molecular Biology 131
- Materials Chemistry 119
- Computational Theory and Mathematics 93
- Infectious Diseases 70
- Plant Science 57
Countries citing papers authored by S. Anusuya
This map shows the geographic impact of S. Anusuya'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 S. Anusuya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Anusuya more than expected).
Fields of papers citing papers by S. Anusuya
This network shows the impact of papers produced by S. Anusuya. 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 S. Anusuya. The network helps show where S. Anusuya may publish in the future.
Co-authorship network of co-authors of S. Anusuya
This figure shows the co-authorship network connecting the top 25 collaborators of S. Anusuya. A scholar is included among the top collaborators of S. Anusuya 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 S. Anusuya. S. Anusuya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 6 | |
| 9 | 32 | |
| 10 | 12 | |
| 11 | 1 | |
| 12 | 13 | |
| 13 | Reading aid for visually impaired people | 1 |
| 14 | 3 | |
| 15 | YEAST GENE EXPRESSION ANALYSIS USING K MEANS AND FCM | 4 |
| 16 | 3 | |
| 17 | 7 | |
| 18 | 6 | |
| 19 | 12 | |
| 20 | 22 |
About S. Anusuya
S. Anusuya is a scholar working on Molecular Medicine, Computational Theory and Mathematics and Infectious Diseases, having authored 41 papers that have together received 398 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Leprosy Research and Treatment (4 papers) and Nanoparticles: synthesis and applications (4 papers). The work is most often cited by research in Computational Theory and Mathematics (93 citations), Infectious Diseases (70 citations) and Complementary and alternative medicine (27 citations). S. Anusuya has collaborated with scholars based in India, Japan and Tanzania. Frequent co-authors include M. Michael Gromiha, V. Anbazhagan, Jeyakumar Natarajan, Devadasan Velmurugan, Nisha Muralidharan, C. V. Ramakrishnan, Suresh K. Rayala, Ramasamy Sakthivel, S. Kannan and S. Akila Parvathy Dharshini. Their work appears in journals such as Applied Biochemistry and Biotechnology, Journal of Molecular Structure and Current Topics in Medicinal Chemistry.
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.