Emma Dann
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
- Immunology top 10%
- Immune cells in cancer
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
Papers in
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- Single-cell and spatial transcriptomics 7
- Gene expression and cancer classification 2
- Bioinformatics and Genomic Networks 1
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- Cancer Genomics and Diagnostics 3
- Co-authors
- Sarah A. Teichmann (5 shared papers)John C. Marioni (3 shared papers)Neil C. Henderson (1 shared paper)Michael D. Morgan (1 shared paper)Roser Vento‐Tormo (2 shared papers)Adam Gayoso (1 shared paper)Jun Sung Park (1 shared paper)Rasa Elmentaite (1 shared paper)
- Journals
- Nature Biotechnology (3 papers)Nature Communications (1 paper)Journal of Clinical Oncology (1 paper)Nature Methods (1 paper)Genome biology (1 paper)
- Partner nations
- United StatesUnited KingdomRussia
In The Last Decade
Emma Dann
12 papers receiving 1.1k citations
Emma Dann's Hit Papers
Peers
Comparison fields: 5 of 94
- Biophysics 106
- Immunology 286
- Cancer Research 193
- Molecular Biology 733
- Neurology 49
Countries citing papers authored by Emma Dann
This map shows the geographic impact of Emma Dann'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 Emma Dann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma Dann more than expected).
Fields of papers citing papers by Emma Dann
This network shows the impact of papers produced by Emma Dann. 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 Emma Dann. The network helps show where Emma Dann may publish in the future.
Co-authors
The 25 scholars most cited alongside Emma Dann, 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 | Cell2location maps fine-grained cell types in spatial transcriptomics Hit paper breakdown → | 2022 | 550 |
| 2 | Differential abundance testing on single-cell data using k-nearest neighbor graphs Hit paper breakdown → | 2021 | 355 |
| 3 | 2020 | 136 | |
| 4 | 2023 | 31 | |
| 5 | 2023 | 25 | |
| 6 | 2024 | 14 | |
| 7 | 2024 | 6 | |
| 8 | 2025 | 4 | |
| 9 | 2024 | 4 | |
| 10 | 2025 | 4 | |
| 11 | 2020 | 2 | |
| 12 | 2020 | 1 | |
| 13 | 2026 | 0 |
About Emma Dann
Emma Dann is a scholar working on Molecular Biology, Cancer Research, Pulmonary and Respiratory Medicine, Biophysics and Immunology, having authored 13 papers that have together received 1.1k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (7 papers), Cancer Genomics and Diagnostics (3 papers), Prostate Cancer Treatment and Research (2 papers), Gene expression and cancer classification (2 papers), T-cell and B-cell Immunology (2 papers), Cell Image Analysis Techniques (2 papers), Childhood Cancer Survivors' Quality of Life (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Biophysics (106 citations), Immunology (286 citations), Cancer Research (193 citations), Molecular Biology (733 citations) and Neurology (49 citations). Emma Dann has collaborated with scholars based in United States, United Kingdom and Russia. Frequent co-authors include Sarah A. Teichmann, John C. Marioni, Neil C. Henderson, Michael D. Morgan, Roser Vento‐Tormo, Adam Gayoso, Jun Sung Park, Rasa Elmentaite, Artem Shmatko and Oliver Stegle. Their work appears in journals such as Nature Biotechnology, Nature Communications, Journal of Clinical Oncology, Nature Methods and Genome 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.