Sandhya Prabhakaran
Impact in
- Oncology top 5%
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
- Immunology top 5%
- Immune cells in cancer
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
Papers in
-
- Single-cell and spatial transcriptomics 6
- Genomics and Phylogenetic Studies 5
- Bioinformatics and Genomic Networks 2
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- Bayesian Methods and Mixture Models 5
- Advanced Clustering Algorithms Research 2
- Co-authors
- Dana Pe’er (4 shared papers)Elham Azizi (4 shared papers)Ambrose Carr (3 shared papers)George Plitas (1 shared paper)Juozas Nainys (1 shared paper)Peter T. McKenney (1 shared paper)Alexander Yu Rudensky (1 shared paper)Kristy Choi (1 shared paper)
- Journals
- Cancer Research (4 papers)Nature Communications (2 papers)Journal of Computational Biology (2 papers)Machine Learning (2 papers)JCI Insight (1 paper)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Sandhya Prabhakaran
24 papers receiving 2.2k citations
Sandhya Prabhakaran's Hit Papers
Peers
Comparison fields: 5 of 84
- Oncology 662
- Immunology 563
- Cancer Research 181
- Molecular Biology 844
- Virology 43
Countries citing papers authored by Sandhya Prabhakaran
This map shows the geographic impact of Sandhya Prabhakaran'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 Sandhya Prabhakaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandhya Prabhakaran more than expected).
Fields of papers citing papers by Sandhya Prabhakaran
This network shows the impact of papers produced by Sandhya Prabhakaran. 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 Sandhya Prabhakaran. The network helps show where Sandhya Prabhakaran may publish in the future.
Co-authors
The 25 scholars most cited alongside Sandhya Prabhakaran, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment Hit paper breakdown → | 2018 | 1525 |
| 2 | 2022 | 132 | |
| 3 | 2014 | 106 | |
| 4 | 2013 | 103 | |
| 5 | Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data. | 2016 | 69 |
| 6 | 2013 | 64 | |
| 7 | 2023 | 53 | |
| 8 | 2021 | 44 | |
| 9 | 2017 | 33 | |
| 10 | 2024 | 24 | |
| 11 | 2022 | 21 | |
| 12 | The Translation-invariant Wishart-Dirichlet Process for Clustering Distance Data | 2010 | 12 |
| 13 | 2012 | 12 | |
| 14 | 2012 | 11 | |
| 15 | 2023 | 4 | |
| 16 | 2013 | 3 | |
| 17 | 2015 | 2 | |
| 18 | 2019 | 2 | |
| 19 | 2022 | 2 | |
| 20 | 2022 | 2 |
About Sandhya Prabhakaran
Sandhya Prabhakaran is a scholar working on Molecular Biology, Artificial Intelligence, Modeling and Simulation, Biophysics and Oncology, having authored 25 papers that have together received 2.2k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (6 papers), Genomics and Phylogenetic Studies (5 papers), Bayesian Methods and Mixture Models (5 papers), Cancer Immunotherapy and Biomarkers (3 papers), Advanced Clustering Algorithms Research (2 papers), Mathematical Biology Tumor Growth (2 papers), Cell Image Analysis Techniques (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Oncology (662 citations), Immunology (563 citations), Cancer Research (181 citations), Molecular Biology (844 citations) and Virology (43 citations). Sandhya Prabhakaran has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Dana Pe’er, Elham Azizi, Ambrose Carr, George Plitas, Juozas Nainys, Peter T. McKenney, Alexander Yu Rudensky, Kristy Choi, Vaidotas Kiseliovas and Krishna Kadaveru. Their work appears in journals such as Cancer Research, Nature Communications, Journal of Computational Biology, Machine Learning and JCI Insight.
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.