Cedrik Magis

620 total citations
12 papers, 382 citations indexed

About

Cedrik Magis is a scholar working on Molecular Biology, Genetics and Information Systems and Management. According to data from OpenAlex, Cedrik Magis has authored 12 papers receiving a total of 382 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 2 papers in Genetics and 1 paper in Information Systems and Management. Recurrent topics in Cedrik Magis's work include Genomics and Phylogenetic Studies (7 papers), RNA and protein synthesis mechanisms (6 papers) and Machine Learning in Bioinformatics (4 papers). Cedrik Magis is often cited by papers focused on Genomics and Phylogenetic Studies (7 papers), RNA and protein synthesis mechanisms (6 papers) and Machine Learning in Bioinformatics (4 papers). Cedrik Magis collaborates with scholars based in Spain, France and Austria. Cedrik Magis's co-authors include Cédric Notredame, Jia‐Ming Chang, Ionas Erb, Giovanni Bussotti, Carsten Kemena, Paolo Di Tommaso, Maria Chatzou, Jose Espinosa‐Carrasco, Jean-François Taly and Evan Floden and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Nature Communications.

In The Last Decade

Cedrik Magis

12 papers receiving 379 citations

Peers

Cedrik Magis

GENET

IMMUN

ECOLO

Marcel Turcotte Canada

C. Lachaize Switzerland

Yunkun Wu China

Simon Dear United Kingdom

T. Šlezak United States

Luca Rappez United States

Tobias Hamp Germany

Natalia Pietrosemoli France

Olga Kunyavskaya Russia

Margaret C. Linak United States

Marcel Turcotte Canada

Cedrik Magis

596 ×2.2

38 ×0.8

GENET

36 ×0.8

28 ×0.7

IMMUN

40 ×1.1

ECOLO

Citations per year, relative to Cedrik Magis Cedrik Magis (= 1×) peers Marcel Turcotte

Countries citing papers authored by Cedrik Magis

Since Specialization

Citations

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

Fields of papers citing papers by Cedrik Magis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cedrik Magis

This figure shows the co-authorship network connecting the top 25 collaborators of Cedrik Magis. A scholar is included among the top collaborators of Cedrik Magis 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 Cedrik Magis. Cedrik Magis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Sasse, Alexander, Debashish Ray, Kaitlin U. Laverty, et al.. (2025). A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function. Nature Biotechnology. 4 indexed citations

Langer, Björn E., et al.. (2025). multistrap: boosting phylogenetic analyses with structural information. Nature Communications. 16(1). 293–293. 3 indexed citations

Tommaso, Paolo Di, Cedrik Magis, Ionas Erb, et al.. (2019). Large multiple sequence alignments with a root-to-leaf regressive method. Nature Biotechnology. 37(12). 1466–1470. 20 indexed citations

Tommaso, Paolo Di, Evan Floden, Cedrik Magis, Emilio Palumbo, & Cédric Notredame. (2017). Nextflow : un outil efficace pour l’amélioration de la stabilité numérique des calculs en analyse génomique. Biologie Aujourd hui. 211(3). 233–237. 4 indexed citations

Floden, Evan, Paolo Di Tommaso, Maria Chatzou, et al.. (2016). PSI/TM-Coffee: a web server for fast and accurate multiple sequence alignments of regular and transmembrane proteins using homology extension on reduced databases. Nucleic Acids Research. 44(W1). W339–W343. 41 indexed citations

Chatzou, Maria, Cedrik Magis, Jia‐Ming Chang, et al.. (2015). Multiple sequence alignment modeling: methods and applications. Briefings in Bioinformatics. 17(6). 1009–1023. 126 indexed citations

Magis, Cedrik, Jean-François Taly, Giovanni Bussotti, et al.. (2013). T-Coffee: Tree-Based Consistency Objective Function for Alignment Evaluation. Methods in molecular biology. 1079. 117–129. 50 indexed citations

Magis, Cedrik, Paolo Di Tommaso, & Cédric Notredame. (2013). T-RMSD: a web server for automated fine-grained protein structural classification. Nucleic Acids Research. 41(W1). W358–W362. 4 indexed citations

Magis, Cedrik, Almer M. van der Sloot, Luis Serrano, & Cédric Notredame. (2012). An improved understanding of TNFL/TNFR interactions using structure-based classifications. Trends in Biochemical Sciences. 37(9). 353–363. 30 indexed citations

10.

Taly, Jean-François, Cedrik Magis, Giovanni Bussotti, et al.. (2011). Using the T-Coffee package to build multiple sequence alignments of protein, RNA, DNA sequences and 3D structures. Nature Protocols. 6(11). 1669–1682. 81 indexed citations

11.

Magis, Cedrik, François Stricher, Almer M. van der Sloot, Luís Serrano, & Cédric Notredame. (2010). T-RMSD: A Fine-grained, Structure-based Classification Method and its Application to the Functional Characterization of TNF Receptors. Journal of Molecular Biology. 400(3). 605–617. 5 indexed citations

12.

Magis, Cedrik, Alain Lecoq, Marie‐Hélène Le Du, et al.. (2006). Structure-Based Secondary Structure-Independent Approach To Design Protein Ligands: Application to the Design of Kv1.2 Potassium Channel Blockers. Journal of the American Chemical Society. 128(50). 16190–16205. 14 indexed citations

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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