Michael Hecker

73 papers receiving 2.3k citations

Michael Hecker's Hit Papers

Gene regulatory network inference: Data integration in dynamic models—A review 2008 · 564 citations
5640+6+12Years since publication100200300400500

Peers

Michael Hecker
Comparison fields: 5 of 138
  • Pathology and Forensic Medicine 647
  • Cancer Research 315
  • Molecular Biology 1.1k
  • Immunology 314
  • Rheumatology 199
Replace Heather P. McDowell with:
Heather P. McDowell United Kingdom
Jeroen A.M. Beliën Netherlands
Hauke Busch Germany
Alexander V. Favorov Russia
Piero Tosi Italy
Jenny C. Taylor United Kingdom
Atanas Kamburov Germany
Peng Wei United States
Chun‐Fang Xu United Kingdom
Minji Jeon South Korea
Michael Hecker relative to Heather P. McDowell United Kingdom Heather P. McDowell's profile →
Citations per field
00.5×2×2.7×
Heather P. McDowell · 1×
Citations per year

Countries citing papers authored by Michael Hecker

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 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 →
2008564
2 2013109
3 2008100
4 201191
5 201668
6 201464
7 201862
8 201960
9 201657
10 201552
11 201248
12 201245
13 201543
14 202040
15 201038
16 201138
17 201037
18 201334
19 201834
20 202133

About Michael Hecker

Michael Hecker is a scholar working on Pathology and Forensic Medicine, Molecular Biology, Immunology, Neurology and Rheumatology, having authored 79 papers that have together received 2.3k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (45 papers), Peripheral Neuropathies and Disorders (10 papers), MicroRNA in disease regulation (8 papers), Rheumatoid Arthritis Research and Therapies (7 papers), Cytokine Signaling Pathways and Interactions (7 papers), RNA Interference and Gene Delivery (5 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and RNA Research and Splicing (5 papers). The work is most often cited by research in Pathology and Forensic Medicine (647 citations), Cancer Research (315 citations), Molecular Biology (1.1k citations), Immunology (314 citations) and Rheumatology (199 citations). Michael Hecker has collaborated with scholars based in Germany, Austria and United Kingdom. Frequent co-authors include Uwe K. Zettl, Reinhard Guthke, Susanne Toepfer, Eugene van Someren, Dirk Koczan, Brit Fitzner, Niklas Frahm, Hans‐Jürgen Thiesen, Brigitte Katrin Paap and Madhan Thamilarasan. Their work appears in journals such as Molecular Neurobiology, Autoimmunity Reviews, Scientific Reports, International Journal of Molecular Sciences 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.

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