Kaj Grandien
- Genetics top 0.1%
- Molecular Biology top 5%
- Endocrinology, Diabetes and Metabolism top 0.5%
- Pathology and Forensic Medicine top 1%
- Reproductive Medicine top 0.5%
- Co-authors
- Jan-Ακε GustafssonGeorge G. J. M. KuiperEva EnmarkStefan NilssonJohan HäggbladBo CarlssonJonathan LindzeyJohn F. Couse
- Topics
- Estrogen and related hormone effects (12 papers)Genetics, Aging, and Longevity in Model Organisms (4 papers)Computational Drug Discovery Methods (2 papers)
- Partner nations
- SwedenGermanyUnited States
In The Last Decade
Kaj Grandien
19 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Genetics 4.7k
- Molecular Biology 1.9k
- Endocrinology, Diabetes and Metabolism 1.5k
- Pathology and Forensic Medicine 1.0k
- Reproductive Medicine 950
Countries citing papers authored by Kaj Grandien
This map shows the geographic impact of Kaj Grandien'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 Kaj Grandien with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaj Grandien more than expected).
Fields of papers citing papers by Kaj Grandien
This network shows the impact of papers produced by Kaj Grandien. 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 Kaj Grandien. The network helps show where Kaj Grandien may publish in the future.
Co-authorship network of co-authors of Kaj Grandien
This figure shows the co-authorship network connecting the top 25 collaborators of Kaj Grandien. A scholar is included among the top collaborators of Kaj Grandien 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 Kaj Grandien. Kaj Grandien is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 13 | |
| 4 | 51 | |
| 5 | 20 | |
| 6 | 78 | |
| 7 | 4 | |
| 8 | 3 | |
| 9 | Comparison of the Ligand Binding Specificity and Transcript Tissue Distribution of Estrogen Receptors α and βbreakdown → | 3762 |
| 10 | 60 | |
| 11 | Human Estrogen Receptor β-Gene Structure, Chromosomal Localization, and Expression Pattern1breakdown → | 887 |
| 12 | 494 | |
| 13 | Tissue Distribution and Quantitative Analysis of Estrogen Receptor-α (ERα) and Estrogen Receptor-β (ERβ) Messenger Ribonucleic Acid in the Wild-Type and ERα-Knockout Mousebreakdown → | 813 |
| 14 | 84 | |
| 15 | 30 | |
| 16 | 27 | |
| 17 | 92 | |
| 18 | 26 | |
| 19 | 46 |
About Kaj Grandien
Kaj Grandien is a scholar working on Aging, Genetics and Reproductive Medicine, having authored 19 papers that have together received 6.5k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (12 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Genetics (4.7k citations), Reproductive Medicine (950 citations) and Endocrinology, Diabetes and Metabolism (1.5k citations). Kaj Grandien has collaborated with scholars based in Sweden, Germany and United States. Frequent co-authors include Jan-Ακε Gustafsson, George G. J. M. Kuiper, Eva Enmark, Stefan Nilsson, Johan Häggblad, Bo Carlsson, Jonathan Lindzey, John F. Couse, Kenneth S. Korach and Katarina Pettersson. Their work appears in journals such as Genes & Development, The Journal of Clinical Endocrinology & Metabolism and Endocrinology.
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.