Leon Hetzel
Impact in
- Molecular Biology top 10%
- Single-cell and spatial transcriptomics
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Genomics and Chromatin Dynamics
Papers in
-
- Neural Networks and Applications 1
- Quantum Information and Cryptography 1
- Machine Learning in Healthcare 1
-
- Computational Drug Discovery Methods 2
- Co-authors
- Stephan Günnemann (4 shared papers)Sven Behnke (1 shared paper)Jan M. Köhler (1 shared paper)Tobias Gindele (1 shared paper)Fabian Joachim Theis (3 shared papers)Mohammad Lotfollahi (2 shared papers)David Sebastian Fischer (1 shared paper)José L. McFaline‐Figueroa (1 shared paper)
- Journals
- Physical Review A (1 paper)Nature Medicine (1 paper)Current Opinion in Systems Biology (1 paper)Molecular Systems Biology (1 paper)Nature Reviews Genetics (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Leon Hetzel
7 papers receiving 890 citations
Leon Hetzel's Hit Papers
Peers
Comparison fields: 5 of 94
- Molecular Biology 534
- Health Informatics 11
- Artificial Intelligence 122
- Biophysics 19
- Computational Theory and Mathematics 35
Countries citing papers authored by Leon Hetzel
This map shows the geographic impact of Leon Hetzel'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 Leon Hetzel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leon Hetzel more than expected).
Fields of papers citing papers by Leon Hetzel
This network shows the impact of papers produced by Leon Hetzel. 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 Leon Hetzel. The network helps show where Leon Hetzel may publish in the future.
Co-authors
The 25 scholars most cited alongside Leon Hetzel, 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 | Best practices for single-cell analysis across modalities Hit paper breakdown → | 2023 | 566 |
| 2 | 2023 | 131 | |
| 3 | 2019 | 104 | |
| 4 | 2021 | 38 | |
| 5 | 2022 | 24 | |
| 6 | 2017 | 20 | |
| 7 | 2024 | 17 | |
| 8 | 2019 | 3 | |
| 9 | 2024 | 0 | |
| 10 | 2026 | 0 |
About Leon Hetzel
Leon Hetzel is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Physical and Theoretical Chemistry and Nuclear Energy and Engineering, having authored 10 papers that have together received 903 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (4 papers), Computational Drug Discovery Methods (2 papers), RNA Interference and Gene Delivery (1 paper), Gene Regulatory Network Analysis (1 paper), Neural Networks and Applications (1 paper), Advanced Physical and Chemical Molecular Interactions (1 paper), Quantum Information and Cryptography (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Molecular Biology (534 citations), Health Informatics (11 citations), Artificial Intelligence (122 citations), Biophysics (19 citations) and Computational Theory and Mathematics (35 citations). Leon Hetzel has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Stephan Günnemann, Sven Behnke, Jan M. Köhler, Tobias Gindele, Fabian Joachim Theis, Mohammad Lotfollahi, David Sebastian Fischer, José L. McFaline‐Figueroa, Riza M. Daza and David López-Paz. Their work appears in journals such as Physical Review A, Nature Medicine, Current Opinion in Systems Biology, Molecular Systems Biology and Nature Reviews Genetics.
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.