Daniel Strobl
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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- Immune Cell Function and Interaction 3
- Immunotherapy and Immune Responses 2
- interferon and immune responses 1
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- Single-cell and spatial transcriptomics 2
- Gene expression and cancer classification 1
- Co-authors
- Fabian J. Theis (3 shared papers)Malte D. Luecken (2 shared papers)Kridsadakorn Chaichoompu (1 shared paper)Martin Dugas (1 shared paper)Luke Zappia (1 shared paper)Anna Danese (1 shared paper)Maria Colomé‐Tatché (1 shared paper)Maren Büttner (1 shared paper)
- Journals
- Nature Methods (1 paper)Science Advances (1 paper)NAR Genomics and Bioinformatics (1 paper)Frontiers in Immunology (1 paper)Blood (1 paper)
- Partner nations
- GermanyNetherlandsUnited Kingdom
In The Last Decade
Daniel Strobl
5 papers receiving 600 citations
Daniel Strobl's Hit Papers
Peers
Comparison fields: 5 of 77
- Biophysics 155
- Molecular Biology 504
- Cancer Research 103
- Immunology 133
- Neurology 18
Countries citing papers authored by Daniel Strobl
This map shows the geographic impact of Daniel Strobl'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 Daniel Strobl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Strobl more than expected).
Fields of papers citing papers by Daniel Strobl
This network shows the impact of papers produced by Daniel Strobl. 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 Daniel Strobl. The network helps show where Daniel Strobl may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Strobl, 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 | 2023 | 36 | |
| 3 | 2023 | 14 | |
| 4 | 2022 | 4 | |
| 5 | 2018 | 4 |
About Daniel Strobl
Daniel Strobl is a scholar working on Immunology, Molecular Biology, Biophysics, Cancer Research and Oncology, having authored 5 papers that have together received 602 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (3 papers), Single-cell and spatial transcriptomics (2 papers), Cell Image Analysis Techniques (2 papers), NF-κB Signaling Pathways (2 papers), Immunotherapy and Immune Responses (2 papers), interferon and immune responses (1 paper), Gene expression and cancer classification (1 paper) and Advanced Fluorescence Microscopy Techniques (1 paper). The work is most often cited by research in Biophysics (155 citations), Molecular Biology (504 citations), Cancer Research (103 citations), Immunology (133 citations) and Neurology (18 citations). Daniel Strobl has collaborated with scholars based in Germany, Netherlands and United Kingdom. Frequent co-authors include Fabian J. Theis, Malte D. Luecken, Kridsadakorn Chaichoompu, Martin Dugas, Luke Zappia, Anna Danese, Maria Colomé‐Tatché, Maren Büttner, Martin Mueller and Marta Interlandi. Their work appears in journals such as Nature Methods, Science Advances, NAR Genomics and Bioinformatics, Frontiers in Immunology and Blood.
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.