Bernhard Steiert
Impact in
- Health Informatics top 10%
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
-
- Gene Regulatory Network Analysis 5
- Microbial Metabolic Engineering and Bioproduction 3
- Bioinformatics and Genomic Networks 2
- Protein Structure and Dynamics 2
-
- Machine Learning in Healthcare 3
- Co-authors
- Lucy Hutchinson (3 shared papers)Jitao David Zhang (1 shared paper)Tony Kam‐Thong (1 shared paper)Solveig Badillo (1 shared paper)Fabian Birzele (1 shared paper)Juliane Siebourg‐Polster (1 shared paper)Balázs Bánfai (1 shared paper)Iakov I. Davydov (1 shared paper)
- Journals
- CPT Pharmacometrics & Systems Pharmacology (3 papers)PLoS Computational Biology (3 papers)PLoS ONE (2 papers)Bioinformatics (2 papers)BMC Systems Biology (1 paper)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Bernhard Steiert
14 papers receiving 1.0k citations
Bernhard Steiert's Hit Papers
Peers
Comparison fields: 5 of 176
- Health Informatics 16
- Biophysics 51
- Modeling and Simulation 27
- Molecular Biology 360
- Statistics and Probability 39
Countries citing papers authored by Bernhard Steiert
This map shows the geographic impact of Bernhard Steiert'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 Bernhard Steiert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard Steiert more than expected).
Fields of papers citing papers by Bernhard Steiert
This network shows the impact of papers produced by Bernhard Steiert. 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 Bernhard Steiert. The network helps show where Bernhard Steiert may publish in the future.
Co-authors
The 25 scholars most cited alongside Bernhard Steiert, 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 | An Introduction to Machine Learning Hit paper breakdown → | 2020 | 531 |
| 2 | 2015 | 156 | |
| 3 | 2016 | 70 | |
| 4 | 2015 | 51 | |
| 5 | 2012 | 48 | |
| 6 | 2014 | 44 | |
| 7 | 2018 | 39 | |
| 8 | 2018 | 34 | |
| 9 | 2016 | 30 | |
| 10 | 2022 | 18 | |
| 11 | 2016 | 17 | |
| 12 | 2019 | 5 | |
| 13 | 2023 | 3 | |
| 14 | 2024 | 3 | |
| 15 | 2025 | 0 |
About Bernhard Steiert
Bernhard Steiert is a scholar working on Molecular Biology, Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics and Statistical and Nonlinear Physics, having authored 15 papers that have together received 1.0k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (5 papers), Machine Learning in Healthcare (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Statistical Methods in Clinical Trials (2 papers), Bioinformatics and Genomic Networks (2 papers), Protein Structure and Dynamics (2 papers), Computational Drug Discovery Methods (2 papers) and Pharmacogenetics and Drug Metabolism (1 paper). The work is most often cited by research in Health Informatics (16 citations), Biophysics (51 citations), Modeling and Simulation (27 citations), Molecular Biology (360 citations) and Statistics and Probability (39 citations). Bernhard Steiert has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Lucy Hutchinson, Jitao David Zhang, Tony Kam‐Thong, Solveig Badillo, Fabian Birzele, Juliane Siebourg‐Polster, Balázs Bánfai, Iakov I. Davydov, Clemens Kreutz and Jens Timmer. Their work appears in journals such as CPT Pharmacometrics & Systems Pharmacology, PLoS Computational Biology, PLoS ONE, Bioinformatics and BMC Systems Biology.
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.