Dhananjay Bhaskar
Impact in
-
- Cellular Mechanics and Interactions
-
- Mathematical Biology Tumor Growth
Papers in
-
- Single-cell and spatial transcriptomics 2
- Protein Structure and Dynamics 2
-
- Computational Drug Discovery Methods 2
- Topological and Geometric Data Analysis 2
- Co-authors
- Ian Y. Wong (4 shared papers)Thomas Valentin (2 shared papers)Leah Edelstein‐Keshet (2 shared papers)Smita Krishnaswamy (5 shared papers)Susan E. Leggett (2 shared papers)Blanche C. Ip (1 shared paper)Theodora Myrto Perdikari (1 shared paper)Amanda Khoo (1 shared paper)
- Journals
- Trends in Immunology (1 paper)Polymer Chemistry (1 paper)Proceedings of the National Academy of Sciences (1 paper)Nature Machine Intelligence (1 paper)Frontiers in Psychiatry (1 paper)
- Partner nations
- United StatesCanadaSweden
In The Last Decade
Dhananjay Bhaskar
15 papers receiving 240 citations
Peers
Comparison fields: 5 of 83
- Cell Biology 71
- Modeling and Simulation 15
- Molecular Medicine 12
- Biophysics 13
- Biomaterials 25
Countries citing papers authored by Dhananjay Bhaskar
This map shows the geographic impact of Dhananjay Bhaskar'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 Dhananjay Bhaskar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dhananjay Bhaskar more than expected).
Fields of papers citing papers by Dhananjay Bhaskar
This network shows the impact of papers produced by Dhananjay Bhaskar. 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 Dhananjay Bhaskar. The network helps show where Dhananjay Bhaskar may publish in the future.
Co-authors
The 25 scholars most cited alongside Dhananjay Bhaskar, 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 | 2019 | 57 | |
| 2 | 2022 | 44 | |
| 3 | 2019 | 33 | |
| 4 | 2018 | 33 | |
| 5 | 2019 | 25 | |
| 6 | 2017 | 15 | |
| 7 | 2023 | 12 | |
| 8 | 2023 | 9 | |
| 9 | 2022 | 7 | |
| 10 | 2023 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2026 | 1 | |
| 14 | Structure-Activity Relationships using Locally Linear Embedding Assisted by Support Vector and Lazy Learning Regressors # | 2004 | 1 |
| 15 | 2017 | 1 | |
| 16 | 2025 | 0 |
About Dhananjay Bhaskar
Dhananjay Bhaskar is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cell Biology, Cellular and Molecular Neuroscience and Ecology, Evolution, Behavior and Systematics, having authored 16 papers that have together received 242 indexed citations. Recurring topics across this work include Cellular Mechanics and Interactions (4 papers), Single-cell and spatial transcriptomics (2 papers), Axon Guidance and Neuronal Signaling (2 papers), Protein Structure and Dynamics (2 papers), Computational Drug Discovery Methods (2 papers), Topological and Geometric Data Analysis (2 papers), Cell Image Analysis Techniques (2 papers) and Biocrusts and Microbial Ecology (2 papers). The work is most often cited by research in Cell Biology (71 citations), Modeling and Simulation (15 citations), Molecular Medicine (12 citations), Biophysics (13 citations) and Biomaterials (25 citations). Dhananjay Bhaskar has collaborated with scholars based in United States, Canada and Sweden. Frequent co-authors include Ian Y. Wong, Thomas Valentin, Leah Edelstein‐Keshet, Smita Krishnaswamy, Susan E. Leggett, Blanche C. Ip, Theodora Myrto Perdikari, Amanda Khoo, T. Arthur Chang and Shun-Ping Wang. Their work appears in journals such as Trends in Immunology, Polymer Chemistry, Proceedings of the National Academy of Sciences, Nature Machine Intelligence and Frontiers in Psychiatry.
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.