Jean-François Gibrat
- Molecular Biology top 5%
- Materials Chemistry top 10%
- Food Science top 5%
- Genetics top 10%
- Ecology top 10%
- Co-authors
- Barry RobsonJean GarnierJ. GarnierJuliette MartinValérie BiouJonathan M. LevinJosselin GarnierValentin Loux
- Topics
- Protein Structure and Dynamics (15 papers)Genomics and Phylogenetic Studies (13 papers)RNA and protein synthesis mechanisms (12 papers)
- Partner nations
- FranceUnited StatesMorocco
In The Last Decade
Jean-François Gibrat
33 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Molecular Biology 1.9k
- Materials Chemistry 391
- Food Science 305
- Genetics 220
- Ecology 170
Countries citing papers authored by Jean-François Gibrat
This map shows the geographic impact of Jean-François Gibrat'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 Jean-François Gibrat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean-François Gibrat more than expected).
Fields of papers citing papers by Jean-François Gibrat
This network shows the impact of papers produced by Jean-François Gibrat. 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 Jean-François Gibrat. The network helps show where Jean-François Gibrat may publish in the future.
Co-authorship network of co-authors of Jean-François Gibrat
This figure shows the co-authorship network connecting the top 25 collaborators of Jean-François Gibrat. A scholar is included among the top collaborators of Jean-François Gibrat 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 Jean-François Gibrat. Jean-François Gibrat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 53 | |
| 4 | 52 | |
| 5 | 14 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 8 | |
| 9 | 3 | |
| 10 | 14 | |
| 11 | BioWorkFlow: Web Services toolkit and workflow applications evaluation to deploy a confidence network | 1 |
| 12 | 23 | |
| 13 | 130 | |
| 14 | 1 | |
| 15 | From GeneWeaver to Agmial | 1 |
| 16 | 5 | |
| 17 | [32] GOR method for predicting protein secondary structure from amino acid sequencebreakdown → | 1031 |
| 18 | 167 | |
| 19 | 1 | |
| 20 | 452 |
About Jean-François Gibrat
Jean-François Gibrat is a scholar working on Molecular Biology, Information Systems and Management and Periodontics, having authored 34 papers that have together received 2.4k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (15 papers), Genomics and Phylogenetic Studies (13 papers) and RNA and protein synthesis mechanisms (12 papers). The work is most often cited by research in Molecular Biology (1.9k citations), Food Science (305 citations) and Microbiology (84 citations). Jean-François Gibrat has collaborated with scholars based in France, United States and Morocco. Frequent co-authors include Barry Robson, Jean Garnier, J. Garnier, Juliette Martin, Valérie Biou, Jonathan M. Levin, Josselin Garnier, Valentin Loux, Jean-François Taly and Antoine Marin. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Bioinformatics.
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.