Archana G. Chavan
- Molecular Biology
- Endocrine and Autonomic Systems top 10%
- Plant Science
- Cellular and Molecular Neuroscience
- Materials Chemistry
- Co-authors
- Andy LiWangJoel HeislerSusan S. GoldenJerry TsaiCarrie L. PartchSarvind TripathiYong‐Gang ChangNicolette F. Goularte
- Topics
- Circadian rhythm and melatonin (9 papers)Photosynthetic Processes and Mechanisms (9 papers)Photoreceptor and optogenetics research (6 papers)
- Partner nations
- United StatesIndia
In The Last Decade
Archana G. Chavan
19 papers receiving 405 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 316
- Endocrine and Autonomic Systems 104
- Plant Science 84
- Cellular and Molecular Neuroscience 81
- Materials Chemistry 42
Countries citing papers authored by Archana G. Chavan
This map shows the geographic impact of Archana G. Chavan'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 Archana G. Chavan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Archana G. Chavan more than expected).
Fields of papers citing papers by Archana G. Chavan
This network shows the impact of papers produced by Archana G. Chavan. 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 Archana G. Chavan. The network helps show where Archana G. Chavan may publish in the future.
Co-authorship network of co-authors of Archana G. Chavan
This figure shows the co-authorship network connecting the top 25 collaborators of Archana G. Chavan. A scholar is included among the top collaborators of Archana G. Chavan 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 Archana G. Chavan. Archana G. Chavan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 45 | |
| 6 | 2 | |
| 7 | 14 | |
| 8 | 11 | |
| 9 | 12 | |
| 10 | 116 | |
| 11 | 8 | |
| 12 | Exploring the molecular architecture of proteins: Method developments in structure prediction and design | 1 |
| 13 | 124 | |
| 14 | 20 | |
| 15 | 5 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | 9 | |
| 19 | 11 |
About Archana G. Chavan
Archana G. Chavan is a scholar working on Endocrine and Autonomic Systems, Cellular and Molecular Neuroscience and Molecular Biology, having authored 19 papers that have together received 408 indexed citations. Recurring topics across this work include Circadian rhythm and melatonin (9 papers), Photosynthetic Processes and Mechanisms (9 papers) and Photoreceptor and optogenetics research (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (104 citations), Molecular Biology (316 citations) and Biotechnology (39 citations). Archana G. Chavan has collaborated with scholars based in United States and India. Frequent co-authors include Andy LiWang, Joel Heisler, Susan S. Golden, Jerry Tsai, Carrie L. Partch, Sarvind Tripathi, Yong‐Gang Chang, Nicolette F. Goularte, Alicia K. Michael and Susan E. Cohen. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Molecular Biology.
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.