Fabian J. Theis
- Biophysics top 0.01%
- Cell Image Analysis Techniques 43
- Molecular Biology top 0.05%
- Single-cell and spatial transcriptomics 120
- Gene Regulatory Network Analysis 73
- Bioinformatics and Genomic Networks 46
- Gene expression and cancer classification 44
- Cancer Research top 0.1%
- Immunology top 0.5%
- Developmental Neuroscience top 0.5%
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- Blind Source Separation Techniques 61
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- Spectroscopy and Chemometric Analyses 32
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- Neural Networks and Applications 29
- Co-authors
- F. Alexander WolfPhilipp AngererMalte D. LueckenFlorian BuettnerMaren BüttnerLaleh HaghverdiJan KrumsiekVolker Bergen
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Fabian J. Theis
436 papers receiving 30.6k citations
Hit Papers
Peers
Comparison fields: 5 of 217
- Biophysics 3.7k
- Molecular Biology 21.1k
- Cancer Research 4.4k
- Immunology 4.4k
- Developmental Neuroscience 790
Countries citing papers authored by Fabian J. Theis
This map shows the geographic impact of Fabian J. Theis'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 Fabian J. Theis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabian J. Theis more than expected).
Fields of papers citing papers by Fabian J. Theis
This network shows the impact of papers produced by Fabian J. Theis. 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 Fabian J. Theis. The network helps show where Fabian J. Theis may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fabian J. Theis, 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 | 2024 | 1 | |
| 2 | 2024 | 43 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 34 | |
| 5 | 2022 | 54 | |
| 6 | 2022 | 6 | |
| 7 | CellRank for directed single-cell fate mappingbreakdown → | 2022 | 282 |
| 8 | 2021 | 164 | |
| 9 | 2020 | 21 | |
| 10 | 2020 | 4 | |
| 11 | 2020 | 56 | |
| 12 | 2020 | 64 | |
| 13 | 2020 | 116 | |
| 14 | 2018 | 16 | |
| 15 | 2018 | 1 | |
| 16 | 2017 | 12 | |
| 17 | 2016 | 49 | |
| 18 | 2015 | 133 | |
| 19 | destiny : diffusion maps for large-scale single-cell data in Rbreakdown → | 2015 | 359 |
| 20 | 2010 | 58 |
About Fabian J. Theis
Fabian J. Theis is a scholar working on Biophysics, Signal Processing and Molecular Biology, having authored 447 papers that have together received 30.9k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (120 papers), Gene Regulatory Network Analysis (73 papers), Blind Source Separation Techniques (61 papers), Bioinformatics and Genomic Networks (46 papers), Gene expression and cancer classification (44 papers), Cell Image Analysis Techniques (43 papers), Spectroscopy and Chemometric Analyses (32 papers) and Neural Networks and Applications (29 papers). The work is most often cited by research in Biophysics (3.7k citations), Molecular Biology (21.1k citations) and Cancer Research (4.4k citations). Fabian J. Theis has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include F. Alexander Wolf, Philipp Angerer, Malte D. Luecken, Florian Buettner, Maren Büttner, Laleh Haghverdi, Jan Krumsiek, Volker Bergen, Marius Lange and Gökçen Eraslan. Their work appears in journals such as Nature, Science and Cell.
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.