S. C. Basak
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Bioinformatics
- Fractal and DNA sequence analysis
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Protein Structure and Dynamics
Papers in
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- RNA and protein synthesis mechanisms 4
- Fractal and DNA sequence analysis 3
- Machine Learning in Bioinformatics 3
- vaccines and immunoinformatics approaches 2
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- Computational Drug Discovery Methods 6
- Co-authors
- Ashesh Nandy (6 shared papers)Milan Randić (1 shared paper)Marjan Vračko (1 shared paper)Denise Mills (3 shared papers)Moiz Mumtaz (1 shared paper)Brian D. Gute (2 shared papers)Nenad Trinajstić (1 shared paper)I. Lukovits (1 shared paper)
- Journals
- SAR and QSAR in environmental research (5 papers)Computers in Biology and Medicine (1 paper)Journal of Chemical Information and Computer Sciences (2 papers)AIP conference proceedings (1 paper)
- Partner nations
- United StatesIndiaHungary
In The Last Decade
S. C. Basak
11 papers receiving 345 citations
Peers
Comparison fields: 5 of 48
- Computational Theory and Mathematics 107
- Molecular Biology 258
- Geometry and Topology 33
- Organic Chemistry 57
- Pharmaceutical Science 10
Countries citing papers authored by S. C. Basak
This map shows the geographic impact of S. C. Basak'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. C. Basak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. C. Basak more than expected).
Fields of papers citing papers by S. C. Basak
This network shows the impact of papers produced by S. C. Basak. 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. C. Basak. The network helps show where S. C. Basak may publish in the future.
Co-authors
The 15 scholars most cited alongside S. C. Basak, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2000 | 216 | |
| 2 | 2007 | 34 | |
| 3 | 2000 | 27 | |
| 4 | 2001 | 26 | |
| 5 | 2001 | 25 | |
| 6 | 2006 | 14 | |
| 7 | 2020 | 9 | |
| 8 | 2006 | 6 | |
| 9 | 2007 | 4 | |
| 10 | 2020 | 2 | |
| 11 | 2017 | 2 |
About S. C. Basak
S. C. Basak is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Pharmacology and Infectious Diseases, having authored 11 papers that have together received 365 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Free Radicals and Antioxidants (5 papers), RNA and protein synthesis mechanisms (4 papers), Fractal and DNA sequence analysis (3 papers), Machine Learning in Bioinformatics (3 papers), vaccines and immunoinformatics approaches (2 papers), Cholinesterase and Neurodegenerative Diseases (2 papers) and Chemical Thermodynamics and Molecular Structure (2 papers). The work is most often cited by research in Computational Theory and Mathematics (107 citations), Molecular Biology (258 citations), Geometry and Topology (33 citations), Organic Chemistry (57 citations) and Pharmaceutical Science (10 citations). S. C. Basak has collaborated with scholars based in United States, India and Hungary. Frequent co-authors include Ashesh Nandy, Milan Randić, Marjan Vračko, Denise Mills, Moiz Mumtaz, Brian D. Gute, Nenad Trinajstić, I. Lukovits, Sonja Nikolić and Dorota Bielińska-Wąż. Their work appears in journals such as SAR and QSAR in environmental research, Computers in Biology and Medicine, Journal of Chemical Information and Computer Sciences and AIP conference proceedings.
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.