Thomas Westerling
Impact in
- Endocrine and Autonomic Systems top 10%
- Circadian rhythm and melatonin
- Aging top 10%
Papers in
- Oncology 5
- Cytokine Signaling Pathways and Interactions 2
- HER2/EGFR in Cancer Research 2
- Co-authors
- Myles Brown (7 shared papers)Shannon T. Bailey (3 shared papers)Kiran Padmanabhan (1 shared paper)Charles J. Weitz (1 shared paper)Emilia Kuuluvainen (1 shared paper)María S. Robles (1 shared paper)Xiaole Shirley Liu (1 shared paper)Hyunjin Shin (1 shared paper)
- Journals
- Toxicologic Pathology (3 papers)Proceedings of the National Academy of Sciences (2 papers)Acta Neuropathologica Communications (1 paper)Nature Communications (1 paper)Laboratory Investigation (1 paper)
- Partner nations
- United StatesFinlandGermany
In The Last Decade
Thomas Westerling
18 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 81
- Endocrine and Autonomic Systems 102
- Aging 26
- Oncology 345
- Cancer Research 177
- Molecular Biology 623
Countries citing papers authored by Thomas Westerling
This map shows the geographic impact of Thomas Westerling'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 Thomas Westerling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Westerling more than expected).
Fields of papers citing papers by Thomas Westerling
This network shows the impact of papers produced by Thomas Westerling. 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 Thomas Westerling. The network helps show where Thomas Westerling may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Westerling, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 182 | |
| 2 | 2012 | 131 | |
| 3 | 2010 | 124 | |
| 4 | 2012 | 120 | |
| 5 | 2017 | 106 | |
| 6 | 2007 | 99 | |
| 7 | 2017 | 92 | |
| 8 | 2014 | 71 | |
| 9 | 2018 | 49 | |
| 10 | 2016 | 25 | |
| 11 | 2004 | 23 | |
| 12 | 2022 | 19 | |
| 13 | 2021 | 19 | |
| 14 | 2014 | 17 | |
| 15 | 2020 | 14 | |
| 16 | 2021 | 10 | |
| 17 | 2021 | 6 | |
| 18 | 2024 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2024 | 0 |
About Thomas Westerling
Thomas Westerling is a scholar working on Molecular Biology, Oncology, Artificial Intelligence, Genetics and Plant Science, having authored 20 papers that have together received 1.1k indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Estrogen and related hormone effects (4 papers), Cytokine Signaling Pathways and Interactions (2 papers), Immunotoxicology and immune responses (2 papers), HER2/EGFR in Cancer Research (2 papers), Cancer-related molecular mechanisms research (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Endocrine and Autonomic Systems (102 citations), Aging (26 citations), Oncology (345 citations), Cancer Research (177 citations) and Molecular Biology (623 citations). Thomas Westerling has collaborated with scholars based in United States, Finland and Germany. Frequent co-authors include Myles Brown, Shannon T. Bailey, Kiran Padmanabhan, Charles J. Weitz, Emilia Kuuluvainen, María S. Robles, Xiaole Shirley Liu, Hyunjin Shin, Tomi P. Mäkelä and Jussi Tuusa. Their work appears in journals such as Toxicologic Pathology, Proceedings of the National Academy of Sciences, Acta Neuropathologica Communications, Nature Communications and Laboratory Investigation.
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.