Jacques Dainat
- Plant Science top 10%
- Chromosomal and Genetic Variations 6
- Pharmacology top 10%
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- Mitochondrial Function and Pathology 12
- Genomics and Phylogenetic Studies 10
- RNA modifications and cancer 4
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- Thyroid Disorders and Treatments 11
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- Neuroscience and Neuropharmacology Research 4
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- Adipose Tissue and Metabolism 4
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- Metabolism and Genetic Disorders 3
- Co-authors
- Jens C. FrisvadKristian Fog NielsenMhairi WorkmanJens NielsenBoyang JiSietske GrijseelsSylvain PrigentJ. Legrand
- Partner nations
- FranceSwedenUnited States
In The Last Decade
Jacques Dainat
41 papers receiving 834 citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Plant Science 308
- Pharmacology 118
- Molecular Biology 445
- Endocrinology, Diabetes and Metabolism 106
- Genetics 151
Countries citing papers authored by Jacques Dainat
This map shows the geographic impact of Jacques Dainat'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 Jacques Dainat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacques Dainat more than expected).
Fields of papers citing papers by Jacques Dainat
This network shows the impact of papers produced by Jacques Dainat. 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 Jacques Dainat. The network helps show where Jacques Dainat may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jacques Dainat, 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 | 2024 | 4 | |
| 2 | 2023 | 3 | |
| 3 | TEsorter: An accurate and fast method to classify LTR-retrotransposons in plant genomesbreakdown → | 2022 | 131 |
| 4 | 2022 | 37 | |
| 5 | 2021 | 2 | |
| 6 | 2020 | 41 | |
| 7 | 2019 | 8 | |
| 8 | 2019 | 71 | |
| 9 | 2019 | 62 | |
| 10 | 2018 | 17 | |
| 11 | 2017 | 196 | |
| 12 | 2017 | 8 | |
| 13 | 2014 | 23 | |
| 14 | 2014 | 4 | |
| 15 | 2012 | 5 | |
| 16 | 1991 | 7 | |
| 17 | [Properties of skeletal muscle fibers. II. Hormonal influences]. | 1989 | 7 |
| 18 | 1988 | 2 | |
| 19 | 1978 | 1 | |
| 20 | [Influence of neonatal hyperthyroidism on the in vivo incorporation of L 3 H-leucine in cerebellar proteins of young rats]. | 1971 | 2 |
About Jacques Dainat
Jacques Dainat is a scholar working on Endocrinology, Diabetes and Metabolism, Clinical Biochemistry and Molecular Biology, having authored 44 papers that have together received 866 indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (12 papers), Thyroid Disorders and Treatments (11 papers), Genomics and Phylogenetic Studies (10 papers), Chromosomal and Genetic Variations (6 papers), Neuroscience and Neuropharmacology Research (4 papers), Adipose Tissue and Metabolism (4 papers), RNA modifications and cancer (4 papers) and Metabolism and Genetic Disorders (3 papers). The work is most often cited by research in Plant Science (308 citations), Pharmacology (118 citations) and Molecular Biology (445 citations). Jacques Dainat has collaborated with scholars based in France, Sweden and United States. Frequent co-authors include Jens C. Frisvad, Kristian Fog Nielsen, Mhairi Workman, Jens Nielsen, Boyang Ji, Sietske Grijseels, Sylvain Prigent, Jens Nielsen, J. Legrand and Guangyuan Li. Their work appears in journals such as PLoS ONE, The Journal of Comparative Neurology and Current Biology.
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.