Frédéric Bard

5.6k total citations
56 papers, 3.9k citations indexed

About

Frédéric Bard is a scholar working on Molecular Biology, Cell Biology and Immunology. According to data from OpenAlex, Frédéric Bard has authored 56 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 27 papers in Cell Biology and 10 papers in Immunology. Recurrent topics in Frédéric Bard's work include Cellular transport and secretion (17 papers), Glycosylation and Glycoproteins Research (10 papers) and Galectins and Cancer Biology (7 papers). Frédéric Bard is often cited by papers focused on Cellular transport and secretion (17 papers), Glycosylation and Glycoproteins Research (10 papers) and Galectins and Cancer Biology (7 papers). Frédéric Bard collaborates with scholars based in Singapore, United States and France. Frédéric Bard's co-authors include Joanne Chia, Vivek Malhotra, Frédéric Saltel, Pierre Jurdic, Olivier Destaing, David J. Gill, Henrik Clausen, Jean-Christophe Géminard, Germaine Goh and Emilie A. Bard-Chapeau and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Frédéric Bard

56 papers receiving 3.9k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Frédéric Bard 2.9k 1.4k 601 398 270 56 3.9k
Letizia Lanzetti 2.2k 0.7× 1.4k 1.0× 362 0.6× 658 1.7× 443 1.6× 39 3.6k
Ritva Tikkanen 2.1k 0.7× 1.6k 1.1× 416 0.7× 271 0.7× 198 0.7× 81 3.3k
Kouichi Tachibana 2.2k 0.8× 1.0k 0.7× 890 1.5× 400 1.0× 247 0.9× 70 3.7k
Brian A. Pollok 2.6k 0.9× 459 0.3× 818 1.4× 617 1.6× 328 1.2× 41 4.0k
Jan Gettemans 2.1k 0.7× 1.2k 0.9× 333 0.6× 319 0.8× 208 0.8× 94 3.3k
Sara Sigismund 3.9k 1.3× 2.0k 1.5× 693 1.2× 1.3k 3.4× 535 2.0× 38 5.9k
Toshiki Itoh 2.9k 1.0× 1.9k 1.4× 177 0.3× 325 0.8× 275 1.0× 75 4.0k
Karl‐Johan Leuchowius 2.3k 0.8× 616 0.4× 363 0.6× 394 1.0× 203 0.8× 15 3.2k
Hai‐Tao He 2.8k 1.0× 750 0.5× 1.8k 3.0× 442 1.1× 290 1.1× 72 4.8k
Keiko Furukawa 3.9k 1.3× 1.2k 0.9× 1.5k 2.5× 349 0.9× 390 1.4× 132 5.4k

Countries citing papers authored by Frédéric Bard

Since Specialization
Citations

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

Fields of papers citing papers by Frédéric Bard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frédéric Bard

This figure shows the co-authorship network connecting the top 25 collaborators of Frédéric Bard. A scholar is included among the top collaborators of Frédéric Bard 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 Frédéric Bard. Frédéric Bard 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.
Tran, Le Son, Joanne Chia, Xavier Le Guezennec, et al.. (2025). ER O-glycosylation in synovial fibroblasts drives cartilage degradation. Nature Communications. 16(1). 2535–2535. 2 indexed citations
2.
Tay, Felicia P., Omar Loss, Laurent Pons, et al.. (2024). Botulinum toxin intoxication requires retrograde transport and membrane translocation at the ER in RenVM neurons. eLife. 12. 1 indexed citations
3.
Wong, Hui Hui, et al.. (2023). Tonic repression of collagen I by the bradykinin receptor 2 in skin fibroblasts. Matrix Biology. 118. 110–128. 5 indexed citations
4.
Tang, Yew Chung, Alvin Wei Tian Ng, John R. McPherson, et al.. (2018). Functional genomics identifies specific vulnerabilities in PTEN-deficient breast cancer. Breast Cancer Research. 20(1). 22–22. 18 indexed citations
5.
Hussain, Shaista, Xavier Le Guezennec, Yi Wang, et al.. (2017). Digging deep into Golgi phenotypic diversity with unsupervised machine learning. Molecular Biology of the Cell. 28(25). 3686–3698. 7 indexed citations
6.
Gordon, David E., et al.. (2017). VAMP3/Syb and YKT6 are required for the fusion of constitutive secretory carriers with the plasma membrane. PLoS Genetics. 13(4). e1006698–e1006698. 31 indexed citations
7.
Bard, Frédéric & Joanne Chia. (2016). Cracking the Glycome Encoder: Signaling, Trafficking, and Glycosylation. Trends in Cell Biology. 26(5). 379–388. 68 indexed citations
8.
Gonzales, Kevin Andrew Uy, Hongqing Liang, Yee Siang Lim, et al.. (2015). Deterministic Restriction on Pluripotent State Dissolution by Cell-Cycle Pathways. Cell. 162(3). 564–579. 152 indexed citations
9.
Goh, Germaine, et al.. (2015). The Ubiquitin Ligase CBLC Maintains the Network Organization of the Golgi Apparatus. PLoS ONE. 10(9). e0138789–e0138789. 7 indexed citations
10.
Jeyakani, Justin, Guillaume Bourque, Frédéric Bard, et al.. (2015). Functional features of EVI1 and EVI1Δ324 isoforms of MECOM gene in genome-wide transcription regulation and oncogenicity. Oncogene. 35(18). 2311–2321. 17 indexed citations
11.
Wright, Graham, et al.. (2015). Nuclear envelope-associated endosomes deliver surface proteins to the nucleus. Nature Communications. 6(1). 8218–8218. 59 indexed citations
12.
Ackema, Karin B., Jürgen Hench, Stefan Böckler, et al.. (2014). The small GTP ase Arf1 modulates mitochondrial morphology and function. The EMBO Journal. 33(22). 2659–2675. 71 indexed citations
13.
Dejeans, Nicolas, Serge N. Manié, Claudio Hetz, et al.. (2014). Addicted to secrete – novel concepts and targets in cancer therapy. Trends in Molecular Medicine. 20(5). 242–250. 69 indexed citations
14.
Lee, Kee Khoon, Terence Hung, Ivor W. Tsang, et al.. (2011). Exploratory analysis of cell-based screening data for phenotype identification in drug-siRNA study. International Journal of Computational Biology and Drug Design. 4(2). 194–194. 3 indexed citations
15.
Gill, David J., et al.. (2010). Regulation of O -glycosylation through Golgi-to-ER relocation of initiation enzymes. The Journal of Cell Biology. 189(5). 843–858. 158 indexed citations
16.
Chia, Na‐Yu, Yun-Shen Chan, Bo Feng, et al.. (2010). A genome-wide RNAi screen reveals determinants of human embryonic stem cell identity. Nature. 468(7321). 316–320. 367 indexed citations
17.
Bard, Frédéric, Arrate Mallabiabarrena, Kota Saito, et al.. (2006). Functional genomics reveals genes involved in protein secretion and Golgi organization. Nature. 439(7076). 604–607. 291 indexed citations
18.
Destaing, Olivier, Frédéric Saltel, Jean-Christophe Géminard, Pierre Jurdic, & Frédéric Bard. (2003). Podosomes Display Actin Turnover and Dynamic Self-Organization in Osteoclasts Expressing Actin-Green Fluorescent Protein. Molecular Biology of the Cell. 14(2). 407–416. 381 indexed citations
19.
Bard, Frédéric, et al.. (2003). Src Regulates Golgi Structure and KDEL Receptor-dependent Retrograde Transport to the Endoplasmic Reticulum. Journal of Biological Chemistry. 278(47). 46601–46606. 89 indexed citations
20.
Bard, Frédéric, et al.. (2002). Molecular complexes that contain both c-Cbl and c-Src associate with Golgi membranes. European Journal of Cell Biology. 81(1). 26–35. 38 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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