Marcel Scheideler
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Aging top 5%
Papers in
-
- MicroRNA in disease regulation 22
- Cancer-related molecular mechanisms research 4
- Physiology 31
- Adipose Tissue and Metabolism 24
- Telomeres, Telomerase, and Senescence 7
- Co-authors
- Michael Karbiener (27 shared papers)Ez‐Zoubir Amri (14 shared papers)Zlatko Trajanoski (13 shared papers)Gerard P. Ailhaud (6 shared papers)Christian Dani (6 shared papers)Peter Opriessnig (3 shared papers)Andreas Prokesch (8 shared papers)Christine Papak (7 shared papers)
In The Last Decade
Marcel Scheideler
80 papers receiving 4.5k citations
Peers
Comparison fields: 5 of 121
- Cancer Research 1.1k
- Aging 74
- Genetics 336
- Physiology 973
- Molecular Biology 1.4k
Countries citing papers authored by Marcel Scheideler
This map shows the geographic impact of Marcel Scheideler'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 Marcel Scheideler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcel Scheideler more than expected).
Fields of papers citing papers by Marcel Scheideler
This network shows the impact of papers produced by Marcel Scheideler. 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 Marcel Scheideler. The network helps show where Marcel Scheideler may publish in the future.
Co-authors
The 25 scholars most cited alongside Marcel Scheideler, 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 80 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 379 | |
| 2 | 2007 | 324 | |
| 3 | 2010 | 322 | |
| 4 | 2018 | 200 | |
| 5 | 2002 | 192 | |
| 6 | 2008 | 175 | |
| 7 | 2013 | 151 | |
| 8 | 2010 | 150 | |
| 9 | 2000 | 119 | |
| 10 | 2011 | 118 | |
| 11 | microRNA miR-27b impairs human adipocyte differentiation and targets PPARg | 2010 | 117 |
| 12 | 2019 | 117 | |
| 13 | 1998 | 114 | |
| 14 | 2005 | 110 | |
| 15 | 2013 | 105 | |
| 16 | 2014 | 100 | |
| 17 | 2010 | 97 | |
| 18 | 2008 | 91 | |
| 19 | 2019 | 87 | |
| 20 | 2017 | 83 |
About Marcel Scheideler
Marcel Scheideler is a scholar working on Cancer Research, Physiology, Molecular Biology, Genetics and Epidemiology, having authored 80 papers that have together received 4.5k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (24 papers), MicroRNA in disease regulation (22 papers), Adipokines, Inflammation, and Metabolic Diseases (9 papers), Telomeres, Telomerase, and Senescence (7 papers), Gene expression and cancer classification (6 papers), Peroxisome Proliferator-Activated Receptors (4 papers), Viral Infectious Diseases and Gene Expression in Insects (4 papers) and Cancer-related molecular mechanisms research (4 papers). The work is most often cited by research in Cancer Research (1.1k citations), Aging (74 citations), Genetics (336 citations), Physiology (973 citations) and Molecular Biology (1.4k citations). Marcel Scheideler has collaborated with scholars based in Austria, Germany and France. Frequent co-authors include Michael Karbiener, Ez‐Zoubir Amri, Zlatko Trajanoski, Gerard P. Ailhaud, Christian Dani, Peter Opriessnig, Andreas Prokesch, Christine Papak, Johannes Grillari and Fátima Sánchez‐Cabo. Their work appears in journals such as BMC Genomics, EMBO Reports, International Journal of Molecular Sciences, Journal of Biotechnology and Aging 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.