Yann Guermeur

1.1k total citations
17 papers, 640 citations indexed

About

Yann Guermeur is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yann Guermeur has authored 17 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Molecular Biology and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yann Guermeur's work include Machine Learning and Algorithms (6 papers), Machine Learning in Bioinformatics (4 papers) and Protein Structure and Dynamics (4 papers). Yann Guermeur is often cited by papers focused on Machine Learning and Algorithms (6 papers), Machine Learning in Bioinformatics (4 papers) and Protein Structure and Dynamics (4 papers). Yann Guermeur collaborates with scholars based in France, Germany and United States. Yann Guermeur's co-authors include J. Mark Cock, Bernhard Gschloessl, C. Geourjon, Patrick Gallinari, Gilbert Deléage, Nicolas Sapay, André Elisseeff, Dominique Zelus, Hélène Paugam‐Moisy and Walter Blondel and has published in prestigious journals such as Bioinformatics, Optics Express and BMC Bioinformatics.

In The Last Decade

Yann Guermeur

16 papers receiving 618 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Yann Guermeur France	8	369	97	86	86	71	17	640
Sabine Cornelsen Germany	8	769 2.1×	118 1.2×	236 2.7×	14 0.2×	52 0.7×	20	962
Xiaowei Zhang China	18	452 1.2×	15 0.2×	108 1.3×	21 0.2×	49 0.7×	30	924
Wanting Zhang China	15	249 0.7×	20 0.2×	48 0.6×	27 0.3×	5 0.1×	81	662
Ashoka D. Polpitiya United States	12	1.1k 2.9×	56 0.6×	80 0.9×	9 0.1×	5 0.1×	20	1.4k
А. В. Селиверстов Russia	11	209 0.6×	18 0.2×	69 0.8×	75 0.9×	6 0.1×	57	357
Cheng Shen China	18	328 0.9×	9 0.1×	66 0.8×	34 0.4×	15 0.2×	63	989
Patrick Flick United States	7	488 1.3×	4 0.0×	67 0.8×	53 0.6×	21 0.3×	13	848
Xiaoqiu Huang United States	3	602 1.6×	12 0.1×	59 0.7×	86 1.0×	6 0.1×	3	860
Ganesan Pugalenthi India	21	877 2.4×	7 0.1×	68 0.8×	126 1.5×	29 0.4×	39	1.2k
Lennart Björkesten Sweden	6	650 1.8×	9 0.1×	23 0.3×	25 0.3×	58 0.8×	7	1.1k

Countries citing papers authored by Yann Guermeur

Since Specialization

Citations

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

Fields of papers citing papers by Yann Guermeur

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yann Guermeur

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

All Works

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17 of 17 papers shown

Guermeur, Yann, et al.. (2022). ProtNAff: protein-bound Nucleic Acid filters and fragment libraries. Bioinformatics. 38(16). 3911–3917. 1 indexed citations

Lauer, Fabien, et al.. (2019). Rademacher complexity and generalization performance of multi-category margin classifiers. Neurocomputing. 342. 6–15. 5 indexed citations

Guermeur, Yann. (2018). Rademacher complexity of margin multi-category classifiers. Neural Computing and Applications. 32(24). 17995–18008.

Guermeur, Yann. (2017). L-norm Sauer–Shelah lemma for margin multi-category classifiers. Journal of Computer and System Sciences. 89. 450–473. 8 indexed citations

Guermeur, Yann, et al.. (2011). Hybrid feature selection and SVM-based classification for mouse skin precancerous stages diagnosis from bimodal spectroscopy. Optics Express. 20(1). 228–228. 17 indexed citations

Guermeur, Yann. (2010). Sample Complexity of Classifiers Taking Values in ℝ^Q, Application to Multi-Class SVMs. Communication in Statistics- Theory and Methods. 39(3). 543–557. 7 indexed citations

Guermeur, Yann, et al.. (2008). VC Theory of Large Margin Multi-Category Classifiers. HAL (Le Centre pour la Communication Scientifique Directe). 9 indexed citations

Gschloessl, Bernhard, Yann Guermeur, & J. Mark Cock. (2008). HECTAR: A method to predict subcellular targeting in heterokonts. BMC Bioinformatics. 9(1). 393–393. 167 indexed citations

Sapay, Nicolas, Yann Guermeur, & Gilbert Deléage. (2006). Prediction of amphipathic in-plane membrane anchors in monotopic proteins using a SVM classifier. BMC Bioinformatics. 7(1). 255–255. 125 indexed citations

10.

Guermeur, Yann, André Elisseeff, & Dominique Zelus. (2005). A comparative study of multi‐class support vector machines in the unifying framework of large margin classifiers. Applied Stochastic Models in Business and Industry. 21(2). 199–214. 4 indexed citations

11.

Guermeur, Yann. (2004). Large Margin Multi-category Discriminant Models and Scale-sensitive Psi-dimensions. HAL (Le Centre pour la Communication Scientifique Directe). 47. 1 indexed citations

12.

Guermeur, Yann, Gianluca Pollastri, André Elisseeff, et al.. (2003). Combining protein secondary structure prediction models with ensemble methods of optimal complexity. Neurocomputing. 56. 305–327. 20 indexed citations

13.

Guermeur, Yann. (2002). Combining Discriminant Models with New Multi-Class SVMs. Pattern Analysis and Applications. 5(2). 168–179. 75 indexed citations

14.

Paugam‐Moisy, Hélène, André Elisseeff, & Yann Guermeur. (2000). Generalization performance of multiclass discriminant models. 177–182 vol.4. 4 indexed citations

15.

Guermeur, Yann, et al.. (1999). Improved performance in protein secondary structure prediction by inhomogeneous score combination.. Bioinformatics. 15(5). 413–421. 185 indexed citations

16.

Guermeur, Yann. (1999). Estimating the sample complexity of a multi-class discriminant model. 1999. 310–315. 6 indexed citations

17.

Gascuel, Olivier, Bernadette Bouchon‐Meunier, Gilles Caraux, et al.. (1998). Twelve Numerical, Symbolic and Hybrid Supervised Classification Methods. International Journal of Pattern Recognition and Artificial Intelligence. 12(5). 517–571. 6 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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