David Schnoerr
Impact in
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- Nonlinear Dynamics and Pattern Formation
Papers in
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- Gene Regulatory Network Analysis 8
- Single-cell and spatial transcriptomics 2
- Bioinformatics and Genomic Networks 2
- Diffusion and Search Dynamics 2
- Microbial Metabolic Engineering and Bioproduction 1
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- Cellular Automata and Applications 2
- Co-authors
- Michael P. H. Stumpf (4 shared papers)Mark Isalan (1 shared paper)Guido Sanguinetti (3 shared papers)Ramon Grima (3 shared papers)Sean T. Vittadello (1 shared paper)Rowan D. Brackston (1 shared paper)David F. Anderson (1 shared paper)Heike Siebert (1 shared paper)
- Journals
- Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (1 paper)Journal of Mathematical Biology (1 paper)PLoS Computational Biology (1 paper)Journal of Physics A Mathematical and Theoretical (1 paper)Nature Communications (1 paper)
- Partner nations
- United KingdomAustraliaGermany
In The Last Decade
David Schnoerr
9 papers receiving 158 citations
Peers
Comparison fields: 5 of 50
- Computer Networks and Communications 48
- Biophysics 10
- Modeling and Simulation 7
- Molecular Biology 100
- Statistical and Nonlinear Physics 17
Countries citing papers authored by David Schnoerr
This map shows the geographic impact of David Schnoerr'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 David Schnoerr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Schnoerr more than expected).
Fields of papers citing papers by David Schnoerr
This network shows the impact of papers produced by David Schnoerr. 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 David Schnoerr. The network helps show where David Schnoerr may publish in the future.
Co-authors
The 11 scholars most cited alongside David Schnoerr, 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 | 2019 | 61 | |
| 2 | 2021 | 29 | |
| 3 | 2020 | 22 | |
| 4 | 2016 | 22 | |
| 5 | 2020 | 9 | |
| 6 | 2021 | 7 | |
| 7 | 2019 | 5 | |
| 8 | 2017 | 5 | |
| 9 | 2017 | 2 |
About David Schnoerr
David Schnoerr is a scholar working on Molecular Biology, Computational Theory and Mathematics, Computer Networks and Communications, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 9 papers that have together received 162 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (8 papers), Single-cell and spatial transcriptomics (2 papers), Bioinformatics and Genomic Networks (2 papers), Diffusion and Search Dynamics (2 papers), Cellular Automata and Applications (2 papers), COVID-19 epidemiological studies (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper) and Neuroscience and Neural Engineering (1 paper). The work is most often cited by research in Computer Networks and Communications (48 citations), Biophysics (10 citations), Modeling and Simulation (7 citations), Molecular Biology (100 citations) and Statistical and Nonlinear Physics (17 citations). David Schnoerr has collaborated with scholars based in United Kingdom, Australia and Germany. Frequent co-authors include Michael P. H. Stumpf, Mark Isalan, Guido Sanguinetti, Ramon Grima, Sean T. Vittadello, Rowan D. Brackston, David F. Anderson, Heike Siebert, Matthias H. Hennig and Michael E. Rule. Their work appears in journals such as Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal of Mathematical Biology, PLoS Computational Biology, Journal of Physics A Mathematical and Theoretical and Nature Communications.
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.