Predict (France)

249 papers and 7.3k indexed citations i.

About

In recent decades, authors affiliated with Predict (France) have published 249 papers, which have received a total of 7.3k indexed citations. Scholars at this organization have produced 38 papers in Molecular Biology, 33 papers in Global and Planetary Change and 30 papers in Oncology on the topics of Climate variability and models (21 papers), Cancer Genomics and Diagnostics (15 papers) and Meteorological Phenomena and Simulations (15 papers). Their work is cited by papers focused on Global and Planetary Change (1.7k citations), Atmospheric Science (1.7k citations) and Molecular Biology (1.0k citations). Authors at Predict (France) collaborate with scholars in France, United States and United Kingdom and have published in prestigious journals including Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Applied Physics Letters. Some of Predict (France)'s most productive authors include Anne Maı̂tre, Vincent Prévot, Sébastien G. Bouret, Bénédicte Dehouck, David P. Rowell, Amandine Mullier, V. F. Zakharov, Г. В. Алексеев, A. P. Nagurnyi and Leonid Bobylev.

In The Last Decade

Fields of papers published by authors at Predict (France)

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Predict (France) at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Predict (France) at the time of their publication.

Countries citing scholars working at Predict (France)

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Predict (France). 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 papers produced at Predict (France) with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Predict (France) more than expected).

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.

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2025