Mia Klannemark
- Molecular Biology top 10%
- Physiology top 5%
- Genetics top 5%
- Surgery top 10%
- Epidemiology top 10%
- Co-authors
- Cecilia M. LindgrenCarl G. BrewerDavid AltshulerEric S. LanderStacey BolkCharles R. LaneS. F. SchaffnerThomas J. Hudson
- Topics
- Adipose Tissue and Metabolism (7 papers)Peroxisome Proliferator-Activated Receptors (3 papers)Metabolism, Diabetes, and Cancer (3 papers)
- Cited by
- PhysiologyBiochemistryGenetics
In The Last Decade
Mia Klannemark
11 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Molecular Biology 958
- Physiology 688
- Genetics 569
- Surgery 377
- Epidemiology 290
Countries citing papers authored by Mia Klannemark
This map shows the geographic impact of Mia Klannemark'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 Mia Klannemark with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mia Klannemark more than expected).
Fields of papers citing papers by Mia Klannemark
This network shows the impact of papers produced by Mia Klannemark. 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 Mia Klannemark. The network helps show where Mia Klannemark may publish in the future.
Co-authorship network of co-authors of Mia Klannemark
This figure shows the co-authorship network connecting the top 25 collaborators of Mia Klannemark. A scholar is included among the top collaborators of Mia Klannemark based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mia Klannemark. Mia Klannemark is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | et Lander ES. 2000. The common PPARgamma Prol2Ala polymorphism is associated with decreased risk of type 2 diabetes. Nat Genet Sep; 26 (l): 76-80. American Thoracic Society. 1987. Standards for the diagnosis and care of patients with chronic obstructive pulmonary disease (COPD) and asthma. Am Rev Respir Dis | 2 |
| 2 | 26 | |
| 3 | 16 | |
| 4 | The hormone-sensitive lipase C-60G gene polymorphism is associated with abdominal obesity | 1 |
| 5 | 90 | |
| 6 | 48 | |
| 7 | The common PPARγ Pro12Ala polymorphism is associated with decreased risk of type 2 diabetesbreakdown → | 1310 |
| 8 | 11 | |
| 9 | 181 | |
| 10 | 33 | |
| 11 | 64 |
About Mia Klannemark
Mia Klannemark is a scholar working on Endocrine and Autonomic Systems, Biochemistry and Physiology, having authored 11 papers that have together received 1.8k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (7 papers), Peroxisome Proliferator-Activated Receptors (3 papers) and Metabolism, Diabetes, and Cancer (3 papers). The work is most often cited by research in Physiology (688 citations), Biochemistry (169 citations) and Genetics (569 citations). Mia Klannemark has collaborated with scholars based in Sweden, Finland and France. Frequent co-authors include Cecilia M. Lindgren, Carl G. Brewer, David Altshuler, Eric S. Lander, Stacey Bolk, Charles R. Lane, S. F. Schaffner, Thomas J. Hudson, Joel N. Hirschhorn and Mark J. Daly. Their work appears in journals such as Nature Genetics, Diabetes and Journal of Lipid Research.
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.