Sara Mathieson
Impact in
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- Genetic diversity and population structure
- Forensic and Genetic Research
- Genetic and phenotypic traits in livestock
- Genetic Associations and Epidemiology
- Evolution and Genetic Dynamics
- Genetic Mapping and Diversity in Plants and Animals
Papers in
- Genetics 6
- Genetic and phenotypic traits in livestock 3
- Forensic and Genetic Research 2
- Genetic Associations and Epidemiology 2
- Genetic diversity and population structure 2
- Evolution and Genetic Dynamics 2
- Genomic variations and chromosomal abnormalities 1
- Genetic Mapping and Diversity in Plants and Animals 1
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- Metabolomics and Mass Spectrometry Studies 1
- Co-authors
- Iain Mathieson (3 shared papers)Matteo Fumagalli (2 shared papers)Ulaş Işıldak (1 shared paper)Linda Pattini (1 shared paper)Jiaping Wang (1 shared paper)Michael Κourakos (2 shared papers)Zhanpeng Wang (1 shared paper)Rebecca Riley (1 shared paper)
- Journals
- eLife (1 paper)Molecular Ecology Resources (1 paper)PLoS Computational Biology (1 paper)Molecular Biology and Evolution (1 paper)Genetics (1 paper)
- Partner nations
- United StatesItalyUnited Kingdom
In The Last Decade
Sara Mathieson
6 papers receiving 190 citations
Peers
Comparison fields: 5 of 58
- Genetics 129
- Paleontology 7
- Biochemistry 7
- Molecular Biology 66
- Ecological Modeling 4
Countries citing papers authored by Sara Mathieson
This map shows the geographic impact of Sara Mathieson'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 Sara Mathieson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sara Mathieson more than expected).
Fields of papers citing papers by Sara Mathieson
This network shows the impact of papers produced by Sara Mathieson. 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 Sara Mathieson. The network helps show where Sara Mathieson may publish in the future.
Co-authors
The 13 scholars most cited alongside Sara Mathieson, 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 | 2018 | 75 | |
| 2 | 2019 | 64 | |
| 3 | 2021 | 35 | |
| 4 | 2024 | 10 | |
| 5 | 2021 | 4 | |
| 6 | 2023 | 3 |
About Sara Mathieson
Sara Mathieson is a scholar working on Genetics, Molecular Biology, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Hematology, having authored 6 papers that have together received 191 indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (3 papers), Forensic and Genetic Research (2 papers), Genetic Associations and Epidemiology (2 papers), Genetic diversity and population structure (2 papers), Evolution and Genetic Dynamics (2 papers), Genomic variations and chromosomal abnormalities (1 paper), Genetic Mapping and Diversity in Plants and Animals (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). The work is most often cited by research in Genetics (129 citations), Paleontology (7 citations), Biochemistry (7 citations), Molecular Biology (66 citations) and Ecological Modeling (4 citations). Sara Mathieson has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Iain Mathieson, Matteo Fumagalli, Ulaş Işıldak, Linda Pattini, Jiaping Wang, Michael Κourakos, Zhanpeng Wang, Rebecca Riley, Maja Bućan and Yuval B. Simons. Their work appears in journals such as eLife, Molecular Ecology Resources, PLoS Computational Biology, Molecular Biology and Evolution and Genetics.
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.