Markus W. Covert
Impact in
- Biophysics top 0.1%
- Cell Image Analysis Techniques
- Molecular Biology top 1%
- Microbial Metabolic Engineering and Bioproduction
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Single-cell and spatial transcriptomics
Papers in
-
- Gene Regulatory Network Analysis 32
- Microbial Metabolic Engineering and Bioproduction 26
- Bioinformatics and Genomic Networks 15
- Single-cell and spatial transcriptomics 6
- Co-authors
- Bernhard Ø. PalssonJacob HugheyTakamasa KudoJonathan R. KarrDerek N. MacklinMarkus J. HerrgårdChristophe H. SchillingJeremy S. Edwards
- Journals
- Cell Systems (8 papers)Journal of Theoretical Biology (4 papers)PLoS Computational Biology (4 papers)Biophysical Journal (3 papers)Cell (3 papers)
- Partner nations
- United StatesFrancePoland
In The Last Decade
Markus W. Covert
73 papers receiving 7.8k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Biophysics 1.0k
- Molecular Biology 5.6k
- Immunology 948
- Cancer Research 535
- Structural Biology 44
Countries citing papers authored by Markus W. Covert
This map shows the geographic impact of Markus W. Covert'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 Markus W. Covert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus W. Covert more than expected).
Fields of papers citing papers by Markus W. Covert
This network shows the impact of papers produced by Markus W. Covert. 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 Markus W. Covert. The network helps show where Markus W. Covert may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Markus W. Covert, 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 | 2025 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 20 | |
| 5 | 2022 | 6 | |
| 6 | 2020 | 43 | |
| 7 | 2018 | 10 | |
| 8 | Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments Hit paper breakdown → | 2016 | 337 |
| 9 | 2015 | 44 | |
| 10 | 2014 | 40 | |
| 11 | 2013 | 15 | |
| 12 | 2013 | 17 | |
| 13 | 2011 | 1 | |
| 14 | Single-cell NF-κB dynamics reveal digital activation and analogue information processing Hit paper breakdown → | 2010 | 636 |
| 15 | 2009 | 44 | |
| 16 | Integrating high-throughput and computational data elucidates bacterial networks Hit paper breakdown → | 2004 | 592 |
| 17 | 2003 | 63 | |
| 18 | 2003 | 105 | |
| 19 | 2002 | 236 | |
| 20 | 2001 | 303 |
About Markus W. Covert
Markus W. Covert is a scholar working on Biophysics, Molecular Biology, Cancer Research, Immunology and Microbiology, having authored 74 papers that have together received 8.0k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (32 papers), Microbial Metabolic Engineering and Bioproduction (26 papers), Bioinformatics and Genomic Networks (15 papers), Bacteriophages and microbial interactions (10 papers), Bacterial Genetics and Biotechnology (10 papers), Immune Response and Inflammation (9 papers), Single-cell and spatial transcriptomics (6 papers) and NF-κB Signaling Pathways (6 papers). The work is most often cited by research in Biophysics (1.0k citations), Molecular Biology (5.6k citations), Immunology (948 citations), Cancer Research (535 citations) and Structural Biology (44 citations). Markus W. Covert has collaborated with scholars based in United States, France and Poland. Frequent co-authors include Bernhard Ø. Palsson, Jacob Hughey, Takamasa Kudo, Jonathan R. Karr, Derek N. Macklin, Markus J. Herrgård, Christophe H. Schilling, Jeremy S. Edwards, Timothy K. Lee and Miriam V. Gutschow. Their work appears in journals such as Cell Systems, Journal of Theoretical Biology, PLoS Computational Biology, Biophysical Journal and Cell.
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.