Vaisali Chandrasekar
- Biomedical Engineering
- Molecular Biology
- Organic Chemistry
- Biochemistry top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- Prasanna D. BelurRegupathi IyyaswamiSarada Prasad DakuaAjay Vikram SinghPeter LauxAndreas LuchMohammed Yusuf AnsariShahab Uddin
- Topics
- Edible Oils Quality and Analysis (8 papers)Free Radicals and Antioxidants (7 papers)Computational Drug Discovery Methods (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Hazardous MaterialsFood Chemistry
In The Last Decade
Vaisali Chandrasekar
24 papers receiving 766 citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Biomedical Engineering 181
- Molecular Biology 178
- Organic Chemistry 115
- Biochemistry 81
- Computational Theory and Mathematics 78
Countries citing papers authored by Vaisali Chandrasekar
This map shows the geographic impact of Vaisali Chandrasekar'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 Vaisali Chandrasekar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vaisali Chandrasekar more than expected).
Fields of papers citing papers by Vaisali Chandrasekar
This network shows the impact of papers produced by Vaisali Chandrasekar. 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 Vaisali Chandrasekar. The network helps show where Vaisali Chandrasekar may publish in the future.
Co-authorship network of co-authors of Vaisali Chandrasekar
This figure shows the co-authorship network connecting the top 25 collaborators of Vaisali Chandrasekar. A scholar is included among the top collaborators of Vaisali Chandrasekar 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 Vaisali Chandrasekar. Vaisali Chandrasekar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 3 | |
| 3 | Quantitative prediction of toxicological points of departure using two-stage machine learning models: A new approach methodology (NAM) for chemical risk assessmentbreakdown → | 21 |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 18 | |
| 7 | 26 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 88 | |
| 11 | 48 | |
| 12 | 39 | |
| 13 | 4 | |
| 14 | 58 | |
| 15 | 21 | |
| 16 | 1 | |
| 17 | 46 | |
| 18 | 18 | |
| 19 | 1 | |
| 20 | 131 |
About Vaisali Chandrasekar
Vaisali Chandrasekar is a scholar working on Biochemistry, Computational Theory and Mathematics and Organic Chemistry, having authored 25 papers that have together received 782 indexed citations. Recurring topics across this work include Edible Oils Quality and Analysis (8 papers), Free Radicals and Antioxidants (7 papers) and Computational Drug Discovery Methods (5 papers). The work is most often cited by research in Biochemistry (81 citations), Health Informatics (10 citations) and Biomaterials (71 citations). Vaisali Chandrasekar has collaborated with scholars based in Qatar, India and Germany. Frequent co-authors include Prasanna D. Belur, Regupathi Iyyaswami, Sarada Prasad Dakua, Ajay Vikram Singh, Peter Laux, Andreas Luch, Mohammed Yusuf Ansari, Shahab Uddin, Shidin Balakrishnan and Veronica Tisato. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Hazardous Materials and Food 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.