Anna Danese
Impact in
- Biophysics top 2%
- Cell Image Analysis Techniques
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- Single-cell and spatial transcriptomics
- Gene Regulatory Network Analysis
- Gene expression and cancer classification
- Extracellular vesicles in disease
- Bioinformatics and Genomic Networks
Papers in
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- Single-cell and spatial transcriptomics 5
- Epigenetics and DNA Methylation 2
- CRISPR and Genetic Engineering 2
- Gene expression and cancer classification 1
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- Trypanosoma species research and implications 1
- Co-authors
- Maria Colomé‐Tatché (6 shared papers)Fabian J. Theis (3 shared papers)Kridsadakorn Chaichoompu (2 shared papers)Daniel Strobl (1 shared paper)Martin Dugas (1 shared paper)Malte D. Luecken (1 shared paper)Luke Zappia (1 shared paper)Martin Mueller (1 shared paper)
- Journals
- Nucleic Acids Research (2 papers)Nature Communications (2 papers)Nature Methods (1 paper)Nature Neuroscience (1 paper)Development (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Anna Danese
9 papers receiving 789 citations
Anna Danese's Hit Papers
Peers
Comparison fields: 5 of 83
- Biophysics 163
- Molecular Biology 653
- Cancer Research 110
- Immunology 113
- Neurology 19
Countries citing papers authored by Anna Danese
This map shows the geographic impact of Anna Danese'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 Anna Danese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna Danese more than expected).
Fields of papers citing papers by Anna Danese
This network shows the impact of papers produced by Anna Danese. 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 Anna Danese. The network helps show where Anna Danese may publish in the future.
Co-authors
The 25 scholars most cited alongside Anna Danese, 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 | Benchmarking atlas-level data integration in single-cell genomics Hit paper breakdown → | 2021 | 630 |
| 2 | 2021 | 80 | |
| 3 | 2021 | 52 | |
| 4 | 2024 | 15 | |
| 5 | 2024 | 8 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 1 | |
| 8 | 2025 | 1 | |
| 9 | 2026 | 1 |
About Anna Danese
Anna Danese is a scholar working on Molecular Biology, Epidemiology, Immunology, Cardiology and Cardiovascular Medicine and Hematology, having authored 9 papers that have together received 793 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Epigenetics and DNA Methylation (2 papers), CRISPR and Genetic Engineering (2 papers), Acute Myeloid Leukemia Research (1 paper), Trypanosoma species research and implications (1 paper), Cancer Genomics and Diagnostics (1 paper), Gene expression and cancer classification (1 paper) and Virus-based gene therapy research (1 paper). The work is most often cited by research in Biophysics (163 citations), Molecular Biology (653 citations), Cancer Research (110 citations), Immunology (113 citations) and Neurology (19 citations). Anna Danese has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Maria Colomé‐Tatché, Fabian J. Theis, Kridsadakorn Chaichoompu, Daniel Strobl, Martin Dugas, Malte D. Luecken, Luke Zappia, Martin Mueller, Maren Büttner and Marta Interlandi. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Nature Methods, Nature Neuroscience and Development.
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.