Agata Kubaszek
- Epidemiology top 10%
- Molecular Biology
- Physiology top 10%
- Endocrinology, Diabetes and Metabolism top 10%
- Genetics
- Co-authors
- Markku LaaksoJussi PihlajamäkiPauli KarhapääIlkka VauhkonenJohan G. ErikssonMatti UusitupaHelena HämäläinenPirjo Ilanne‐Parikka
- Topics
- Adipokines, Inflammation, and Metabolic Diseases (4 papers)Adipose Tissue and Metabolism (4 papers)Pancreatic function and diabetes (3 papers)
- Partner nations
- FinlandUnited StatesGermany
In The Last Decade
Agata Kubaszek
11 papers receiving 679 citations
Peers
Comparison fields: 5 of 74
- Epidemiology 257
- Molecular Biology 201
- Physiology 201
- Endocrinology, Diabetes and Metabolism 191
- Genetics 153
Countries citing papers authored by Agata Kubaszek
This map shows the geographic impact of Agata Kubaszek'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 Agata Kubaszek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Agata Kubaszek more than expected).
Fields of papers citing papers by Agata Kubaszek
This network shows the impact of papers produced by Agata Kubaszek. 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 Agata Kubaszek. The network helps show where Agata Kubaszek may publish in the future.
Co-authorship network of co-authors of Agata Kubaszek
This figure shows the co-authorship network connecting the top 25 collaborators of Agata Kubaszek. A scholar is included among the top collaborators of Agata Kubaszek 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 Agata Kubaszek. Agata Kubaszek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 77 | |
| 2 | 36 | |
| 3 | 20 | |
| 4 | 55 | |
| 5 | 41 | |
| 6 | The G-250A promoter polymorphism of the hepatic lipase gene predicts the conversion from impaired glucose tolerance to type 2 diabetes mellitus | 3 |
| 7 | 51 | |
| 8 | 51 | |
| 9 | 200 | |
| 10 | 61 | |
| 11 | 117 | |
| 12 | Kliniczna charakterystyka pacjentów z dyslokacją elektrody stymulatora — doniesienie wstępne | 0 |
About Agata Kubaszek
Agata Kubaszek is a scholar working on Endocrine and Autonomic Systems, Endocrinology, Diabetes and Metabolism and Physiology, having authored 12 papers that have together received 712 indexed citations. Recurring topics across this work include Adipokines, Inflammation, and Metabolic Diseases (4 papers), Adipose Tissue and Metabolism (4 papers) and Pancreatic function and diabetes (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (191 citations), Physiology (201 citations) and Epidemiology (257 citations). Agata Kubaszek has collaborated with scholars based in Finland, United States and Germany. Frequent co-authors include Markku Laakso, Jussi Pihlajamäki, Pauli Karhapää, Ilkka Vauhkonen, Johan G. Eriksson, Matti Uusitupa, Helena Hämäläinen, Pirjo Ilanne‐Parikka, Sirkka Keinänen‐Kiukaanniemi and Jaana Lindström. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Diabetes Care and Diabetes.
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.