Mark Campbell
Impact in
- Physiology top 5%
- Adipose Tissue and Metabolism
- Diet and metabolism studies
- Biochemistry top 5%
Papers in
-
- Peroxisome Proliferator-Activated Receptors 8
- Metabolism, Diabetes, and Cancer 3
- Wnt/β-catenin signaling in development and cancer 2
- Physiology 17
- Adipose Tissue and Metabolism 15
- Co-authors
- Antonio Vidal‐Puig (20 shared papers)Matej Orešič (8 shared papers)Gema Medina‐Gómez (11 shared papers)Sam Virtue (9 shared papers)Margaret Blount (3 shared papers)Sergio Rodríguez‐Cuenca (5 shared papers)Mercedes Jimenez‐Liñan (2 shared papers)Laxman Yetukuri (2 shared papers)
- Journals
- PLoS ONE (3 papers)Diabetes (2 papers)Brain Research (2 papers)Cell Reports (2 papers)Disease Models & Mechanisms (2 papers)
- Partner nations
- United KingdomSpainUnited States
In The Last Decade
Mark Campbell
32 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 112
- Physiology 553
- Biochemistry 125
- Epidemiology 383
- Molecular Biology 731
- Biological Psychiatry 23
Countries citing papers authored by Mark Campbell
This map shows the geographic impact of Mark Campbell'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 Mark Campbell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Campbell more than expected).
Fields of papers citing papers by Mark Campbell
This network shows the impact of papers produced by Mark Campbell. 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 Mark Campbell. The network helps show where Mark Campbell may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Campbell, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 342 | |
| 2 | 2017 | 121 | |
| 3 | 2010 | 82 | |
| 4 | 2008 | 82 | |
| 5 | 2018 | 78 | |
| 6 | 2010 | 75 | |
| 7 | 2005 | 73 | |
| 8 | 1998 | 70 | |
| 9 | 2017 | 69 | |
| 10 | 2015 | 55 | |
| 11 | 2013 | 52 | |
| 12 | 2011 | 47 | |
| 13 | 2012 | 44 | |
| 14 | 2012 | 44 | |
| 15 | 2009 | 37 | |
| 16 | 2021 | 34 | |
| 17 | 2011 | 27 | |
| 18 | 2006 | 22 | |
| 19 | 2012 | 21 | |
| 20 | 2009 | 21 |
About Mark Campbell
Mark Campbell is a scholar working on Molecular Biology, Physiology, Epidemiology, Endocrinology, Diabetes and Metabolism and Genetics, having authored 36 papers that have together received 1.5k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (15 papers), Peroxisome Proliferator-Activated Receptors (8 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers), Metabolism, Diabetes, and Cancer (3 papers), Wnt/β-catenin signaling in development and cancer (2 papers), Hypothalamic control of reproductive hormones (2 papers), Exercise and Physiological Responses (2 papers) and Listeria monocytogenes in Food Safety (2 papers). The work is most often cited by research in Physiology (553 citations), Biochemistry (125 citations), Epidemiology (383 citations), Molecular Biology (731 citations) and Biological Psychiatry (23 citations). Mark Campbell has collaborated with scholars based in United Kingdom, Spain and United States. Frequent co-authors include Antonio Vidal‐Puig, Matej Orešič, Gema Medina‐Gómez, Sam Virtue, Margaret Blount, Sergio Rodríguez‐Cuenca, Mercedes Jimenez‐Liñan, Laxman Yetukuri, Jaswinder K. Sethi and Vanessa Pellegrinelli. Their work appears in journals such as PLoS ONE, Diabetes, Brain Research, Cell Reports and Disease Models & Mechanisms.
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.