Magali Barbier

28 papers and 296 indexed citations i.

About

Magali Barbier is a scholar working on Molecular Biology, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Magali Barbier has authored 28 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Artificial Intelligence and 5 papers in Computer Networks and Communications. Recurrent topics in Magali Barbier’s work include Acute Myeloid Leukemia Research (5 papers), AI-based Problem Solving and Planning (5 papers) and Robotic Path Planning Algorithms (3 papers). Magali Barbier is often cited by papers focused on Acute Myeloid Leukemia Research (5 papers), AI-based Problem Solving and Planning (5 papers) and Robotic Path Planning Algorithms (3 papers). Magali Barbier collaborates with scholars based in France, United States and Austria. Magali Barbier's co-authors include Xavier Ronot, Jean Boutonnât, Anne‐Marie Mariotte, Ahcène Boumendjel, Katharine A. Muirhead, Charles Lesire, D Seigneurin, M Mousseau, Thibault Gateau and Catherine Chabot and has published in prestigious journals such as Brain, Journal of Medicinal Chemistry and BMC Cancer.

In The Last Decade

Co-authorship network of co-authors of Magali Barbier i

Fields of papers citing papers by Magali Barbier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Magali Barbier. 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 Magali Barbier. The network helps show where Magali Barbier may publish in the future.

Countries citing papers authored by Magali Barbier

Since Specialization
Citations

This map shows the geographic impact of Magali Barbier'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 Magali Barbier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Magali Barbier 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