Franz R. Seefried
- Genetics top 2%
- Genetic and phenotypic traits in livestock 34
- Genetic Mapping and Diversity in Plants and Animals 26
- Animal Genetics and Reproduction 4
- Genetic Syndromes and Imprinting 3
- Agronomy and Crop Science top 5%
- Plant Science top 5%
- Genetics and Plant Breeding 13
- Animal Science and Zoology top 10%
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- melanin and skin pigmentation 6
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- RNA regulation and disease 4
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- Neurological diseases and metabolism 3
Franz R. Seefried
47 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 61
- Genetics 1.0k
- Agronomy and Crop Science 233
- Plant Science 500
- Animal Science and Zoology 83
- Cancer Research 112
Countries citing papers authored by Franz R. Seefried
This map shows the geographic impact of Franz R. Seefried'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 Franz R. Seefried with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Franz R. Seefried more than expected).
Fields of papers citing papers by Franz R. Seefried
This network shows the impact of papers produced by Franz R. Seefried. 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 Franz R. Seefried. The network helps show where Franz R. Seefried may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Franz R. Seefried, 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 | 2025 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 5 | |
| 5 | 2022 | 3 | |
| 6 | 2022 | 4 | |
| 7 | 2021 | 6 | |
| 8 | 2021 | 14 | |
| 9 | 2021 | 6 | |
| 10 | 2021 | 4 | |
| 11 | 2020 | 9 | |
| 12 | 2020 | 2 | |
| 13 | 2020 | 9 | |
| 14 | 2020 | 4 | |
| 15 | 2018 | 19 | |
| 16 | Accuracy of 54K to HD gebotype imputation in Brown Swiss cattle | 2013 | 1 |
| 17 | The Impact of Residual Polygenic Effect on Genomic Evaluation | 2010 | 1 |
| 18 | Approximating reliabilities of estimated direct genomic values | 2010 | 5 |
| 19 | Dairy cattle genetic evaluation using genomic information | 2009 | 4 |
| 20 | A simple method for correcting the bias caused by genomic pre-selection in conventional genetic evaluation | 2009 | 5 |
About Franz R. Seefried
Franz R. Seefried is a scholar working on Genetics, Agronomy and Crop Science and Plant Science, having authored 51 papers that have together received 1.1k indexed citations. Recurring topics across this work include Genetic and phenotypic traits in livestock (34 papers), Genetic Mapping and Diversity in Plants and Animals (26 papers), Genetics and Plant Breeding (13 papers), melanin and skin pigmentation (6 papers), RNA regulation and disease (4 papers), Animal Genetics and Reproduction (4 papers), Genetic Syndromes and Imprinting (3 papers) and Neurological diseases and metabolism (3 papers). The work is most often cited by research in Genetics (1.0k citations), Agronomy and Crop Science (233 citations) and Plant Science (500 citations). Franz R. Seefried has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Georg Thaller, Jens Tetens, Peter Lichtner, David Habier, Reinhard Reents, F Reinhardt, Cord Drögemüller, Birgit Gredler, Beat Bapst and Zengting Liu. Their work appears in journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.
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.