Jean−Fred Fontaine

2.5k total citations
63 papers, 1.6k citations indexed

About

Jean−Fred Fontaine is a scholar working on Molecular Biology, Immunology and Allergy and Dermatology. According to data from OpenAlex, Jean−Fred Fontaine has authored 63 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 18 papers in Immunology and Allergy and 12 papers in Dermatology. Recurrent topics in Jean−Fred Fontaine's work include Bioinformatics and Genomic Networks (16 papers), Allergic Rhinitis and Sensitization (13 papers) and Food Allergy and Anaphylaxis Research (12 papers). Jean−Fred Fontaine is often cited by papers focused on Bioinformatics and Genomic Networks (16 papers), Allergic Rhinitis and Sensitization (13 papers) and Food Allergy and Anaphylaxis Research (12 papers). Jean−Fred Fontaine collaborates with scholars based in Germany, France and United States. Jean−Fred Fontaine's co-authors include Miguel A. Andrade‐Navarro, Martin H. Schaefer, Erich E. Wanker, Adriano Barbosa-Silva, Pablo Porras, Arunachalam Vinayagam, Enrique M. Muro, Yves Malthièry, Stéphanie Pons and Silke Frahm and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Clinical Investigation.

In The Last Decade

Jean−Fred Fontaine

60 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean−Fred Fontaine Germany 21 1.1k 168 168 154 144 63 1.6k
Venkata Satagopam Luxembourg 19 1.1k 1.0× 121 0.7× 158 0.9× 80 0.5× 98 0.7× 66 1.6k
Alexandra Keenan United States 9 1.1k 1.0× 90 0.5× 262 1.6× 111 0.7× 153 1.1× 13 1.7k
Dirk Fey Ireland 17 791 0.7× 142 0.8× 129 0.8× 107 0.7× 49 0.3× 44 1.4k
Stanley J. F. Laulederkind United States 23 1.1k 1.0× 56 0.3× 131 0.8× 96 0.6× 294 2.0× 46 1.7k
Wanqiu Chen United States 21 929 0.8× 71 0.4× 123 0.7× 55 0.4× 199 1.4× 48 1.7k
Denis Torre United States 12 1.1k 1.0× 55 0.3× 270 1.6× 80 0.5× 141 1.0× 17 1.6k
James A. Eddy United States 17 948 0.9× 69 0.4× 135 0.8× 66 0.4× 325 2.3× 24 1.8k
John Erol Evangelista United States 11 1.3k 1.2× 92 0.5× 338 2.0× 152 1.0× 161 1.1× 22 2.2k
Nancy Mah Germany 21 1.5k 1.3× 175 1.0× 141 0.8× 42 0.3× 247 1.7× 51 2.0k

Countries citing papers authored by Jean−Fred Fontaine

Since Specialization
Citations

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

Fields of papers citing papers by Jean−Fred Fontaine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean−Fred Fontaine. 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−Fred Fontaine. The network helps show where Jean−Fred Fontaine may publish in the future.

Co-authorship network of co-authors of Jean−Fred Fontaine

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

All Works

20 of 20 papers shown
1.
Andrade‐Navarro, Miguel A., et al.. (2024). Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets. Genome biology. 25(1). 222–222. 1 indexed citations
2.
3.
Albrecht, Steffen, Tommaso Andreani, Miguel A. Andrade‐Navarro, & Jean−Fred Fontaine. (2022). Single-cell specific and interpretable machine learning models for sparse scChIP-seq data imputation. PLoS ONE. 17(7). e0270043–e0270043. 2 indexed citations
4.
Fontaine, Jean−Fred, Matthias Klein, Thomas Hieronymus, et al.. (2021). Posttranslational modifications by ADAM10 shape myeloid antigen-presenting cell homeostasis in the splenic marginal zone. Proceedings of the National Academy of Sciences. 118(38). 7 indexed citations
5.
Andrade‐Navarro, Miguel A., et al.. (2021). Statistical guidelines for quality control of next-generation sequencing techniques. Life Science Alliance. 4(11). e202101113–e202101113. 6 indexed citations
6.
Albrecht, Steffen, et al.. (2021). seqQscorer: automated quality control of next-generation sequencing data using machine learning. Genome biology. 22(1). 75–75. 11 indexed citations
7.
Andreani, Tommaso, Steffen Albrecht, Jean−Fred Fontaine, & Miguel A. Andrade‐Navarro. (2020). Computational identification of cell-specific variable regions in ChIP-seq data. Nucleic Acids Research. 48(9). e53–e53. 4 indexed citations
8.
Akhtar, Junaid, Piyush More, Steffen Albrecht, et al.. (2019). TAF-ChIP: an ultra-low input approach for genome-wide chromatin immunoprecipitation assay. Life Science Alliance. 2(4). e201900318–e201900318. 8 indexed citations
9.
Demoly, Pascal, Isabelle Bossé, Jean−Fred Fontaine, Philippe Bonniaud, & J. Just. (2018). Allergologie : une spécialité à l’heure des parcours de soins. Revue française d'allergologie. 58(5). 373–382. 7 indexed citations
10.
Fontaine, Jean−Fred, et al.. (2017). Evaluation of in vivo and in vitro models of toxicity by comparison of toxicogenomics data with the literature. Methods. 132. 57–65. 8 indexed citations
11.
Fontaine, Jean−Fred & Miguel A. Andrade‐Navarro. (2016). Gene Set to Diseases (GS2D): disease enrichment analysis on human gene sets with literature data. 2(1). 33–33. 20 indexed citations
12.
Kaergel, Eva, Matthias Heinig, Jean−Fred Fontaine, et al.. (2016). A roadmap of constitutive NF-κB activity in Hodgkin lymphoma: Dominant roles of p50 and p52 revealed by genome-wide analyses. Genome Medicine. 8(1). 28–28. 47 indexed citations
13.
Fontaine, Jean−Fred, Josef Priller, Eike Spruth, Carol Perez‐Iratxeta, & Miguel A. Andrade‐Navarro. (2014). Assessment of curated phenotype mining in neuropsychiatric disorder literature. Methods. 74. 90–96. 3 indexed citations
14.
Seltmann, Stefanie, Harald Stachelscheid, Ludger Jansen, et al.. (2013). CELDA - an ontology for the comprehensive representation of cells in complex systems. BMC Bioinformatics. 14(1). 228–228. 12 indexed citations
15.
Stachelscheid, Harald, Stefanie Seltmann, Fritz Lekschas, et al.. (2013). CellFinder: a cell data repository. Nucleic Acids Research. 42(D1). D950–D958. 22 indexed citations
16.
Rousselle, Anthony, Fatimunnisa Qadri, Jean−Fred Fontaine, et al.. (2013). CXCL5 limits macrophage foam cell formation in atherosclerosis. Journal of Clinical Investigation. 123(3). 1343–1347. 92 indexed citations
17.
Fontaine, Jean−Fred, Bernhard Suter, & Miguel A. Andrade‐Navarro. (2011). QiSampler: evaluation of scoring schemes for high-throughput datasets using a repetitive sampling strategy on gold standards. BMC Research Notes. 4(1). 57–57. 3 indexed citations
18.
Fontaine, Jean−Fred, Adriano Barbosa-Silva, Martin H. Schaefer, et al.. (2009). MedlineRanker: flexible ranking of biomedical literature. Nucleic Acids Research. 37(suppl_2). W141–W146. 107 indexed citations
19.
Fontaine, Jean−Fred, Delphine Mirebeau‐Prunier, Brigitte Franc, et al.. (2007). Microarray analysis refines classification of non-medullary thyroid tumours of uncertain malignancy. Oncogene. 27(15). 2228–2236. 28 indexed citations
20.
Legendre, Matthieu, et al.. (2005). Computing expectation values for RNA motifs using discrete convolutions. BMC Bioinformatics. 6(1). 118–118. 7 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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