Fabian J. Theis

82.0k citations
447 papers · 30.9k indexed · 24 hit papers · h-index 85
Topics
Single-cell and spatial transcriptomics (120 papers)Gene Regulatory Network Analysis (73 papers)Blind Source Separation Techniques (61 papers)

In The Last Decade

Fabian J. Theis

436 papers receiving 30.6k citations

Hit Papers

SCANPY: large-scale single-cell gene expression data anal...20152026201820222018202020192019201510002.0k3.0k

Peers

Fabian J. Theis
Comparison fields: 5 of 217
  • Molecular Biology 21.1k
  • Cancer Research 4.4k
  • Immunology 4.4k
  • Biophysics 3.7k
  • Genetics 2.1k
Replace Sarah A. Teichmann with:
Sarah A. Teichmann United Kingdom
Garry P. Nolan United States
Dana Pe’er United States
Mark H. Ellisman United States
Paul Hoffman United States
Avi Ma’ayan United States
Roland Eils Germany
Terence P. Speed Australia
Rafael A. Irizarry United States
Shalev Itzkovitz Israel
Fabian J. Theis relative to Sarah A. Teichmann United Kingdom Sarah A. Teichmann's profile →
Citations per field
00.5×1.5×2.2×
Sarah A. Teichmann · 1×
Citations per year

Countries citing papers authored by Fabian J. Theis

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Fabian J. Theis

This figure shows the co-authorship network connecting the top 25 collaborators of Fabian J. Theis. A scholar is included among the top collaborators of Fabian J. Theis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fabian J. Theis. Fabian J. Theis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 43
3 2
4 34
5 54
6 6
7
CellRank for directed single-cell fate mappingbreakdown →
282
8 164
9 21
10 4
11 56
12 64
13 116
14 16
15 1
16 12
17 49
18 133
19
destiny : diffusion maps for large-scale single-cell data in Rbreakdown →
359
20 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) and Blind Source Separation Techniques (61 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.

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