Meena Subramaniam
- Molecular Biology top 10%
- Immunology top 10%
- Genetics top 10%
- Oncology top 10%
- Cancer Research top 10%
- Co-authors
- Chun YeAlexander MarsonRachel E. GateDimitre R. SimeonovSteven LinKathrin SchumannJeffrey A. BluestoneEric Boyer
- Topics
- Single-cell and spatial transcriptomics (7 papers)Atherosclerosis and Cardiovascular Diseases (2 papers)CRISPR and Genetic Engineering (2 papers)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Meena Subramaniam
11 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Molecular Biology 1.1k
- Immunology 277
- Genetics 276
- Oncology 258
- Cancer Research 162
Countries citing papers authored by Meena Subramaniam
This map shows the geographic impact of Meena Subramaniam'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 Meena Subramaniam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meena Subramaniam more than expected).
Fields of papers citing papers by Meena Subramaniam
This network shows the impact of papers produced by Meena Subramaniam. 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 Meena Subramaniam. The network helps show where Meena Subramaniam may publish in the future.
Co-authorship network of co-authors of Meena Subramaniam
This figure shows the co-authorship network connecting the top 25 collaborators of Meena Subramaniam. A scholar is included among the top collaborators of Meena Subramaniam 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 Meena Subramaniam. Meena Subramaniam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 8 | |
| 3 | 4 | |
| 4 | 12 | |
| 5 | 36 | |
| 6 | 128 | |
| 7 | 28 | |
| 8 | Implementing and Applying Multiplexed Single Cell RNA-sequencing to Reveal Context-specific Effects in Systemic Lupus Erythematosus | 1 |
| 9 | 123 | |
| 10 | Multiplexed droplet single-cell RNA-sequencing using natural genetic variationbreakdown → | 525 |
| 11 | Generation of knock-in primary human T cells using Cas9 ribonucleoproteinsbreakdown → | 533 |
About Meena Subramaniam
Meena Subramaniam is a scholar working on Biophysics, Molecular Biology and Cancer Research, having authored 11 papers that have together received 1.4k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (7 papers), Atherosclerosis and Cardiovascular Diseases (2 papers) and CRISPR and Genetic Engineering (2 papers). The work is most often cited by research in Business and International Management (54 citations), Molecular Biology (1.1k citations) and Biophysics (90 citations). Meena Subramaniam has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Chun Ye, Alexander Marson, Rachel E. Gate, Dimitre R. Simeonov, Steven Lin, Kathrin Schumann, Jeffrey A. Bluestone, Eric Boyer, Jennifer A. Doudna and Lauren Byrnes. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Biotechnology.
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.