Jean‐Louis Franc

1.2k total citations
52 papers, 953 citations indexed

About

Jean‐Louis Franc is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Cell Biology. According to data from OpenAlex, Jean‐Louis Franc has authored 52 papers receiving a total of 953 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 15 papers in Endocrinology, Diabetes and Metabolism and 12 papers in Cell Biology. Recurrent topics in Jean‐Louis Franc's work include Glycosylation and Glycoproteins Research (14 papers), Thyroid Disorders and Treatments (10 papers) and Proteoglycans and glycosaminoglycans research (7 papers). Jean‐Louis Franc is often cited by papers focused on Glycosylation and Glycoproteins Research (14 papers), Thyroid Disorders and Treatments (10 papers) and Proteoglycans and glycosaminoglycans research (7 papers). Jean‐Louis Franc collaborates with scholars based in France, United States and Belgium. Jean‐Louis Franc's co-authors include Denis Becquet, Anne‐Marie François‐Bellan, Sandrine Siffroi‐Fernandez, Annie Giraud, Mireille Ferrand, Valérie Le Fourn, Patricia Niccoli‐Sire, Guy Fayet, Marie‐Pierre Blanchard and Simone Bouchilloux and has published in prestigious journals such as Journal of Biological Chemistry, Biochemistry and Biochemical Journal.

In The Last Decade

Jean‐Louis Franc

51 papers receiving 933 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‐Louis Franc France 19 550 299 150 149 114 52 953
Isabelle Pirson Belgium 25 1.1k 1.9× 377 1.3× 258 1.7× 115 0.8× 94 0.8× 57 1.6k
David Yowe United States 15 864 1.6× 80 0.3× 125 0.8× 214 1.4× 123 1.1× 19 1.3k
Maria Adams United Kingdom 10 851 1.5× 165 0.6× 110 0.7× 288 1.9× 58 0.5× 13 1.2k
Michael Schrey United Kingdom 21 544 1.0× 170 0.6× 43 0.3× 137 0.9× 132 1.2× 47 1.1k
Pamela A. Lochhead United Kingdom 18 1.2k 2.1× 166 0.6× 201 1.3× 167 1.1× 61 0.5× 21 1.6k
Raymond D. Blind United States 18 658 1.2× 211 0.7× 160 1.1× 106 0.7× 140 1.2× 33 1.2k
Victoria P. Knutson United States 17 709 1.3× 132 0.4× 160 1.1× 177 1.2× 83 0.7× 24 1.1k
Debra S. Drust United States 7 611 1.1× 150 0.5× 162 1.1× 78 0.5× 49 0.4× 8 820
Mary Y. Lorenson United States 17 387 0.7× 223 0.7× 105 0.7× 66 0.4× 28 0.2× 45 825
Ilgar Abbaszade United States 10 290 0.5× 169 0.6× 146 1.0× 59 0.4× 54 0.5× 10 953

Countries citing papers authored by Jean‐Louis Franc

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐Louis Franc

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐Louis Franc. 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‐Louis Franc. The network helps show where Jean‐Louis Franc may publish in the future.

Co-authorship network of co-authors of Jean‐Louis Franc

This figure shows the co-authorship network connecting the top 25 collaborators of Jean‐Louis Franc. A scholar is included among the top collaborators of Jean‐Louis Franc 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‐Louis Franc. Jean‐Louis Franc 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.
Becquet, Denis, et al.. (2021). Direct RNA–RNA interaction between Neat1 and RNA targets, as a mechanism for RNAs paraspeckle retention. RNA Biology. 18(11). 2016–2027. 14 indexed citations
2.
Becquet, Denis, et al.. (2021). Identification of RNAs Engaged in Direct RNA-RNA Interaction with a Long Non-Coding RNA. Journal of Visualized Experiments. 1 indexed citations
3.
Becquet, Denis, et al.. (2021). Genome-wide screening of circadian and non-circadian impact of Neat1 genetic deletion. Computational and Structural Biotechnology Journal. 19. 2121–2132. 1 indexed citations
4.
Becquet, Denis, et al.. (2018). RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA. Journal of Visualized Experiments. 39 indexed citations
5.
Becquet, Denis, et al.. (2018). RNA Pull-down Procedure to Identify RNA Targets of a Long Non-coding RNA. Journal of Visualized Experiments. 15 indexed citations
6.
Guillaumond, Fabienne, Denis Becquet, Brigitte Boyer, et al.. (2012). DNA Microarray Analysis and Functional Profile of Pituitary Transcriptome Under Core-Clock Protein BMAL1 Control. Chronobiology International. 29(2). 103–130. 16 indexed citations
7.
Fourn, Valérie Le, Mireille Ferrand, & Jean‐Louis Franc. (2004). Endoproteolytic Cleavage of Human Thyroperoxidase. Journal of Biological Chemistry. 280(6). 4568–4577. 23 indexed citations
8.
Siffroi‐Fernandez, Sandrine, et al.. (2002). Association of the thyrotropin receptor with calnexin, calreticulin and BiP. European Journal of Biochemistry. 269(20). 4930–4937. 39 indexed citations
9.
Siffroi‐Fernandez, Sandrine, et al.. (2001). Role of complex asparagine-linked oligosaccharides in the expression of a functional thyrotropin receptor. Biochemical Journal. 354(2). 331–336. 5 indexed citations
10.
Siffroi‐Fernandez, Sandrine, et al.. (2000). Degradation of Human Thyroperoxidase in the Endoplasmic Reticulum Involves Two Different Pathways Depending on the Folding State of the Protein. Journal of Biological Chemistry. 275(21). 15948–15954. 43 indexed citations
11.
12.
Mas, Eric, et al.. (1997). Investigation of Two Glycosylated Forms of Bile‐Salt‐Dependent Lipase in Human Pancreatic Juice. European Journal of Biochemistry. 243(1-2). 299–305. 6 indexed citations
13.
Mallet, Bernard, Pierre-Jean Lejeune, Nathalie Baudry, et al.. (1995). N-Glycans Modulate in Vivo and in Vitro Thyroid Hormone Synthesis. Journal of Biological Chemistry. 270(50). 29881–29888. 28 indexed citations
14.
Mas, Eric, et al.. (1993). Variation of the glycosylation of human pancreatic bile‐salt‐dependent lipase. European Journal of Biochemistry. 216(3). 807–812. 31 indexed citations
15.
Franc, Jean‐Louis, et al.. (1991). Effect of N‐glycan removal on the enzymatic activity of porcine thyroid peroxidase. European Journal of Biochemistry. 202(2). 501–505. 13 indexed citations
16.
Franc, Jean‐Louis, et al.. (1990). Role of sialic acid residues in crossed immuno‐affinoelectrophoresis of α1‐proteinase inhibitor. FEBS Letters. 262(1). 36–38. 3 indexed citations
17.
Franc, Jean‐Louis, et al.. (1990). Characterization of the two oligosaccharides present in the preferential hormonogenic domain of human thyroglobulin. Biochemical and Biophysical Research Communications. 166(2). 937–944. 7 indexed citations
18.
Giraud, Annie & Jean‐Louis Franc. (1989). Effects of tunicamycin and N-linked oligosaccharide-processing inhibitors on the morphology of cultured porcine thyroid cells.. PubMed. 48(1). 128–34. 9 indexed citations
19.
Malthièry, Yves, et al.. (1989). Thyroglobulin structure and function: recent advances. Biochimie. 71(2). 195–209. 67 indexed citations
20.
Bismuth, J, et al.. (1988). Nuclear T3 Receptor : Depletion by Tunicamycin Despite the Absence of N-Linked Glycan Units in a Murine Preadipocyte Cell Line and Rat Liver. Journal of Receptor Research. 8(5). 683–698. 1 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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