Anna Danese
Impact in
- Molecular Biology top 10%
- Single-cell and spatial transcriptomics
- Genomics and Chromatin Dynamics
- Bioinformatics and Genomic Networks
- Epigenetics and DNA Methylation
- Pluripotent Stem Cells Research
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- Neurogenesis and neuroplasticity mechanisms
Papers in
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- Single-cell and spatial transcriptomics 5
- Pluripotent Stem Cells Research 2
- RNA Research and Splicing 1
- CRISPR and Genetic Engineering 1
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- Acute Myeloid Leukemia Research 2
- Hematopoietic Stem Cell Transplantation 1
- Co-authors
- Maria Colomé‐Tatché (7 shared papers)Fabian Joachim Theis (3 shared papers)Kridsadakorn Chaichoompu (2 shared papers)Malte D. Luecken (1 shared paper)Marta Interlandi (1 shared paper)Maren Büttner (1 shared paper)Daniel C. Strobl (1 shared paper)Martin Dugas (1 shared paper)
- Journals
- Nature Communications (2 papers)Nucleic Acids Research (2 papers)Development (1 paper)HemaSphere (1 paper)Nature Methods (1 paper)
- Partner nations
- GermanyUnited KingdomCanada
In The Last Decade
Anna Danese
10 papers receiving 969 citations
Anna Danese's Hit Papers
Peers
Comparison fields: 5 of 66
- Molecular Biology 779
- Developmental Neuroscience 21
- Hepatology 26
- Health Informatics 5
- Biophysics 13
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 | 782 |
| 2 | 2021 | 92 | |
| 3 | 2021 | 59 | |
| 4 | 2024 | 20 | |
| 5 | 2024 | 8 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 3 | |
| 8 | 2024 | 3 | |
| 9 | 2025 | 1 | |
| 10 | 2026 | 1 |
About Anna Danese
Anna Danese is a scholar working on Molecular Biology, Hematology, Developmental Neuroscience, Epidemiology and Nuclear Energy and Engineering, having authored 10 papers that have together received 976 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Pluripotent Stem Cells Research (2 papers), Acute Myeloid Leukemia Research (2 papers), RNA Research and Splicing (1 paper), Hematopoietic Stem Cell Transplantation (1 paper), Trypanosoma species research and implications (1 paper), Neurogenesis and neuroplasticity mechanisms (1 paper) and CRISPR and Genetic Engineering (1 paper). The work is most often cited by research in Molecular Biology (779 citations), Developmental Neuroscience (21 citations), Hepatology (26 citations), Health Informatics (5 citations) and Biophysics (13 citations). Anna Danese has collaborated with scholars based in Germany, United Kingdom and Canada. Frequent co-authors include Maria Colomé‐Tatché, Fabian Joachim Theis, Kridsadakorn Chaichoompu, Malte D. Luecken, Marta Interlandi, Maren Büttner, Daniel C. Strobl, Martin Dugas, Luke Zappia and David Sebastian Fischer. Their work appears in journals such as Nature Communications, Nucleic Acids Research, Development, HemaSphere and Nature Methods.
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.