Bernhard Steiert

1.7k citations
15 papers · 1.0k · 1 hit paper · h-index 11

Impact in

Papers in

    • Gene Regulatory Network Analysis 6
    • Microbial Metabolic Engineering and Bioproduction 3
    • Protein Structure and Dynamics 2
    • Bioinformatics and Genomic Networks 2
    • Gene expression and cancer classification 2
    • Machine Learning in Healthcare 3

Bernhard Steiert

14 papers receiving 992 citations

Hit Papers

An Introduction to Machine Learning 2020 · 503 citations
5030+2+4Years since publication100200300400500

Peers

Bernhard Steiert
Comparison fields: 5 of 180
  • Health Informatics 23
  • Biophysics 50
  • Modeling and Simulation 30
  • Molecular Biology 383
  • Computational Theory and Mathematics 82
Replace Lucy Hutchinson with:
Lucy Hutchinson Switzerland
Wenbin Liu China
Fredrik Johansson Sweden
Paolo Cazzaniga Italy
Xiong Liu United States
E.R. Dougherty United States
Olga Valenzuela Spain
Marco S. Nobile Italy
Giorgio Valentini Italy
Bernhard Steiert relative to Lucy Hutchinson Switzerland Lucy Hutchinson's profile →
Citations per field
00.5×10×16.3×
Lucy Hutchinson · 1×
Citations per year

Countries citing papers authored by Bernhard Steiert

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Bernhard Steiert Line = papers co-authored together Bernhard Steiert links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
An Introduction to Machine Learning
Hit paper breakdown →
2020503
2 2015153
3 201668
4 201551
5 201247
6 201444
7 201839
8 201833
9 201630
10 202218
11 201617
12 20195
13 20233
14 20241
15 20250

About Bernhard Steiert

Bernhard Steiert is a scholar working on Molecular Biology, Artificial Intelligence, Statistics and Probability, Computational Theory and Mathematics and Management Science and Operations Research, having authored 15 papers that have together received 1.0k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (6 papers), Computational Drug Discovery Methods (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Machine Learning in Healthcare (3 papers), Protein Structure and Dynamics (2 papers), Statistical Methods in Clinical Trials (2 papers), Bioinformatics and Genomic Networks (2 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Health Informatics (23 citations), Biophysics (50 citations), Modeling and Simulation (30 citations), Molecular Biology (383 citations) and Computational Theory and Mathematics (82 citations). Bernhard Steiert has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Lucy Hutchinson, Jitao David Zhang, Fabian Birzele, Balázs Bánfai, Juliane Siebourg‐Polster, Tony Kam‐Thong, Iakov I. Davydov, Solveig Badillo, Jens Timmer and Clemens Kreutz. Their work appears in journals such as PLoS Computational Biology, CPT Pharmacometrics & Systems Pharmacology, Bioinformatics, PLoS ONE and Translational Vision Science & Technology.

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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