Bernhard Steiert
Impact in
- Health Informatics top 10%
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- Statistical Methods in Clinical Trials 2
-
- Gene Regulatory Network Analysis 5
- Microbial Metabolic Engineering and Bioproduction 3
- Bioinformatics and Genomic Networks 2
- Protein Structure and Dynamics 2
- Gene expression and cancer classification 1
- Co-authors
- Lucy G. Hutchinson (3 shared papers)Balázs Bánfai (1 shared paper)Juliane Siebourg‐Polster (1 shared paper)Fabian Birzele (1 shared paper)Jitao David Zhang (1 shared paper)Tony Kam‐Thong (1 shared paper)Solveig Badillo (1 shared paper)Iakov I. Davydov (1 shared paper)
- Journals
- PLoS Computational Biology (3 papers)CPT Pharmacometrics & Systems Pharmacology (3 papers)Bioinformatics (2 papers)Cell Systems (2 papers)PLoS ONE (2 papers)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Bernhard Steiert
16 papers receiving 1.2k citations
Bernhard Steiert's Hit Papers
Peers
Comparison fields: 5 of 178
- Health Informatics 21
- Biophysics 54
- Modeling and Simulation 32
- Molecular Biology 436
- Statistics and Probability 44
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 | 591 |
| 2 | 2015 | 176 | |
| 3 | 2016 | 79 | |
| 4 | 2015 | 57 | |
| 5 | 2012 | 55 | |
| 6 | 2014 | 53 | |
| 7 | 2017 | 45 | |
| 8 | 2018 | 41 | |
| 9 | 2018 | 38 | |
| 10 | 2016 | 32 | |
| 11 | 2016 | 22 | |
| 12 | 2022 | 21 | |
| 13 | 2023 | 5 | |
| 14 | 2024 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2025 | 1 |
About Bernhard Steiert
Bernhard Steiert is a scholar working on Statistics and Probability, Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics and Aging, having authored 16 papers that have together received 1.2k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (5 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Machine Learning in Healthcare (3 papers), Statistical Methods in Clinical Trials (2 papers), Bioinformatics and Genomic Networks (2 papers), Computational Drug Discovery Methods (2 papers), Protein Structure and Dynamics (2 papers) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Health Informatics (21 citations), Biophysics (54 citations), Modeling and Simulation (32 citations), Molecular Biology (436 citations) and Statistics and Probability (44 citations). Bernhard Steiert has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Lucy G. Hutchinson, Balázs Bánfai, Juliane Siebourg‐Polster, Fabian Birzele, Jitao David Zhang, Tony Kam‐Thong, Solveig Badillo, Iakov I. Davydov, Clemens Kreutz and Jens Timmer. Their work appears in journals such as PLoS Computational Biology, CPT Pharmacometrics & Systems Pharmacology, Bioinformatics, Cell Systems and PLoS ONE.
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.