Michael Hecker
Impact in
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- Multiple Sclerosis Research Studies
- Cancer Research top 5%
- MicroRNA in disease regulation
Papers in
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- Multiple Sclerosis Research Studies 43
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- RNA Research and Splicing 6
- Co-authors
- Uwe K. Zettl (64 shared papers)Reinhard Guthke (4 shared papers)Eugene van Someren (1 shared paper)Susanne Toepfer (1 shared paper)Dirk Koczan (21 shared papers)Brit Fitzner (21 shared papers)Niklas Frahm (16 shared papers)Hans‐Jürgen Thiesen (12 shared papers)
- Journals
- Scientific Reports (4 papers)Autoimmunity Reviews (4 papers)International Journal of Molecular Sciences (4 papers)Molecular Neurobiology (4 papers)PLoS ONE (4 papers)
- Partner nations
- GermanyAustriaUnited Kingdom
In The Last Decade
Michael Hecker
69 papers receiving 2.2k citations
Michael Hecker's Hit Papers
Peers
Comparison fields: 5 of 140
- Pathology and Forensic Medicine 648
- Cancer Research 365
- Immunology 378
- Rheumatology 259
- Molecular Biology 1.2k
Countries citing papers authored by Michael Hecker
This map shows the geographic impact of Michael Hecker'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 Michael Hecker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Hecker more than expected).
Fields of papers citing papers by Michael Hecker
This network shows the impact of papers produced by Michael Hecker. 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 Michael Hecker. The network helps show where Michael Hecker may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Hecker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Gene regulatory network inference: Data integration in dynamic models—A review Hit paper breakdown → | 2008 | 511 |
| 2 | 2013 | 104 | |
| 3 | 2008 | 97 | |
| 4 | 2011 | 87 | |
| 5 | 2016 | 63 | |
| 6 | 2014 | 62 | |
| 7 | 2019 | 56 | |
| 8 | 2016 | 55 | |
| 9 | 2018 | 55 | |
| 10 | 2015 | 51 | |
| 11 | 2012 | 47 | |
| 12 | 2015 | 42 | |
| 13 | 2012 | 41 | |
| 14 | 2020 | 37 | |
| 15 | 2011 | 37 | |
| 16 | 2010 | 36 | |
| 17 | 2010 | 35 | |
| 18 | 2013 | 33 | |
| 19 | 2018 | 33 | |
| 20 | 2021 | 32 |
About Michael Hecker
Michael Hecker is a scholar working on Pathology and Forensic Medicine, Molecular Biology, Immunology, Oncology and Rheumatology, having authored 76 papers that have together received 2.2k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (43 papers), Peripheral Neuropathies and Disorders (12 papers), Cytokine Signaling Pathways and Interactions (10 papers), Rheumatoid Arthritis Research and Therapies (10 papers), MicroRNA in disease regulation (9 papers), Systemic Lupus Erythematosus Research (7 papers), RNA Research and Splicing (6 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). The work is most often cited by research in Pathology and Forensic Medicine (648 citations), Cancer Research (365 citations), Immunology (378 citations), Rheumatology (259 citations) and Molecular Biology (1.2k citations). Michael Hecker has collaborated with scholars based in Germany, Austria and United Kingdom. Frequent co-authors include Uwe K. Zettl, Reinhard Guthke, Eugene van Someren, Susanne Toepfer, Dirk Koczan, Brit Fitzner, Niklas Frahm, Hans‐Jürgen Thiesen, Brigitte Katrin Paap and Madhan Thamilarasan. Their work appears in journals such as Scientific Reports, Autoimmunity Reviews, International Journal of Molecular Sciences, Molecular Neurobiology 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.