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
- Protein Degradation and Inhibitors 1
- RNA and protein synthesis mechanisms 1
- Co-authors
- Maria Colomé‐Tatché (6 shared papers)Kridsadakorn Chaichoompu (2 shared papers)Fabian J. Theis (3 shared papers)Martin Dugas (1 shared paper)Luke Zappia (1 shared paper)Malte D. Luecken (1 shared paper)Maren Büttner (1 shared paper)Martin Mueller (1 shared paper)
- Journals
- Nucleic Acids Research (2 papers)Nature Communications (2 papers)Nature Methods (1 paper)HemaSphere (1 paper)Development (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Anna Danese
7 papers receiving 686 citations
Anna Danese's Hit Papers
Peers
Comparison fields: 5 of 85
- Biophysics 163
- Molecular Biology 593
- Cancer Research 120
- Immunology 114
- Developmental Neuroscience 11
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 | 544 |
| 2 | 2021 | 73 | |
| 3 | 2021 | 47 | |
| 4 | 2024 | 14 | |
| 5 | 2024 | 7 | |
| 6 | 2023 | 4 | |
| 7 | 2025 | 1 | |
| 8 | 2023 | 0 |
About Anna Danese
Anna Danese is a scholar working on Molecular Biology, Epidemiology, Immunology, Cardiology and Cardiovascular Medicine and Hematology, having authored 8 papers that have together received 690 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), Cancer Genomics and Diagnostics (1 paper), Cell Image Analysis Techniques (1 paper), Protein Degradation and Inhibitors (1 paper), RNA and protein synthesis mechanisms (1 paper) and Acute Myeloid Leukemia Research (1 paper). The work is most often cited by research in Biophysics (163 citations), Molecular Biology (593 citations), Cancer Research (120 citations), Immunology (114 citations) and Developmental Neuroscience (11 citations). Anna Danese has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Maria Colomé‐Tatché, Kridsadakorn Chaichoompu, Fabian J. Theis, Martin Dugas, Luke Zappia, Malte D. Luecken, Maren Büttner, Martin Mueller, Daniel Strobl and Marta Interlandi. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Nature Methods, HemaSphere 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.