Daniel Ladant

10.0k total citations · 1 hit paper
144 papers, 7.6k citations indexed

About

Daniel Ladant is a scholar working on Molecular Biology, Genetics and Microbiology. According to data from OpenAlex, Daniel Ladant has authored 144 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Molecular Biology, 66 papers in Genetics and 52 papers in Microbiology. Recurrent topics in Daniel Ladant's work include Bacterial Genetics and Biotechnology (63 papers), RNA and protein synthesis mechanisms (47 papers) and Bacterial Infections and Vaccines (45 papers). Daniel Ladant is often cited by papers focused on Bacterial Genetics and Biotechnology (63 papers), RNA and protein synthesis mechanisms (47 papers) and Bacterial Infections and Vaccines (45 papers). Daniel Ladant collaborates with scholars based in France, United States and Italy. Daniel Ladant's co-authors include Gouzel Karimova, Agnès Ullmann, Josette Pidoux, Claude Leclerc, A Ullmann, Peter Šebo, Alexandre Chenal, Nathalie Dautin, Jacques Bellalou and Catherine Fayolle and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Daniel Ladant

139 papers receiving 7.5k citations

Hit Papers

A bacterial two-hybrid sy... 1998 2026 2007 2016 1998 400 800 1.2k

Author Peers

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

Author Last Decade Papers Cites
Daniel Ladant 4.8k 2.8k 2.1k 1.4k 1.1k 144 7.6k
Magdalene So 3.7k 0.8× 2.6k 0.9× 3.1k 1.5× 1.8k 1.3× 882 0.8× 123 8.9k
Michael Koomey 3.4k 0.7× 2.2k 0.8× 2.2k 1.1× 983 0.7× 473 0.4× 99 6.0k
H. Steven Seifert 3.6k 0.8× 2.1k 0.8× 3.7k 1.8× 754 0.6× 683 0.6× 139 7.7k
Raphael H. Valdivia 4.0k 0.8× 1.4k 0.5× 2.0k 1.0× 1.5k 1.1× 1.5k 1.3× 97 9.0k
Joen Luirink 6.4k 1.3× 4.7k 1.7× 670 0.3× 1.3k 0.9× 710 0.6× 181 9.3k
Jukka Finne 4.9k 1.0× 728 0.3× 1.3k 0.6× 885 0.7× 1.2k 1.1× 146 8.3k
M. Alexander Schmidt 2.3k 0.5× 1.1k 0.4× 663 0.3× 2.4k 1.8× 721 0.6× 130 6.0k
Warren W. Wakarchuk 5.2k 1.1× 655 0.2× 495 0.2× 543 0.4× 810 0.7× 156 7.7k
Alexander von Gabain 3.7k 0.8× 1.9k 0.7× 440 0.2× 309 0.2× 880 0.8× 77 5.6k
Françoise Jacob‐Dubuisson 2.0k 0.4× 1.8k 0.6× 1.0k 0.5× 1.2k 0.9× 262 0.2× 87 4.0k

Countries citing papers authored by Daniel Ladant

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Ladant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Ladant

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Ladant. A scholar is included among the top collaborators of Daniel Ladant 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 Daniel Ladant. Daniel Ladant 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.
Dupuis, Gabrielle, et al.. (2025). Interplay between T3SS effectors, ExoY activation, and cGMP signaling in Pseudomonas aeruginosa infection. Nature Communications. 17(1). 69–69.
2.
Karimova, Gouzel, Julien Dairou, Quentin Giai Gianetto, et al.. (2023). Interaction network among de novo purine nucleotide biosynthesis enzymes in Escherichia coli. FEBS Journal. 290(12). 3165–3184. 10 indexed citations
3.
Popoff, Michel R., et al.. (2023). Animal Toxins: A Historical Outlook at the Institut Pasteur of Paris. Toxins. 15(7). 462–462.
4.
Retailleau, Pascal, Martine Comisso, Christophe Velours, et al.. (2023). Functional and structural insights into the multi-step activation and catalytic mechanism of bacterial ExoY nucleotidyl cyclase toxins bound to actin-profilin. PLoS Pathogens. 19(9). e1011654–e1011654. 2 indexed citations
5.
Karimova, Gouzel, Emilie Gauliard, Marilyne Davi, Scot P. Ouellette, & Daniel Ladant. (2023). Protein–Protein Interaction: Bacterial Two Hybrid. Methods in molecular biology. 207–224. 4 indexed citations
6.
Brier, Sébastien, Ariel Méchaly, Sylviane Hoos, et al.. (2022). Dynamics and structural changes of calmodulin upon interaction with the antagonist calmidazolium. BMC Biology. 20(1). 176–176. 14 indexed citations
8.
O’Brien, Darragh P., Sylviane Hoos, Sébastien Brûlé, et al.. (2021). A High‐Affinity Calmodulin‐Binding Site in the CyaA Toxin Translocation Domain is Essential for Invasion of Eukaryotic Cells. Advanced Science. 8(9). 2003630–2003630. 13 indexed citations
9.
Belyy, Alexander, et al.. (2018). The extreme C terminus of the Pseudomonas aeruginosa effector ExoY is crucial for binding to its eukaryotic activator, F-actin. Journal of Biological Chemistry. 293(51). 19785–19796. 14 indexed citations
10.
Ulivieri, Cristina, Anna Onnis, Francesca Finetti, et al.. (2018). Compartmentalized Cyclic AMP Production by the Bordetella pertussis and Bacillus anthracis Adenylate Cyclase Toxins Differentially Affects the Immune Synapse in T Lymphocytes. Frontiers in Immunology. 9. 919–919. 9 indexed citations
11.
Belyy, Alexander, Undine Mechold, Louis Renault, & Daniel Ladant. (2017). ExoY, an actin-activated nucleotidyl cyclase toxin from P. aeruginosa: A minireview. Toxicon. 149. 65–71. 18 indexed citations
12.
O’Brien, Darragh P., D. Durand, Véronique Yvette Ntsogo Enguéné, et al.. (2017). Calcium Tightly Regulates Disorder-To-Order Transitions Involved in the Secretion, Folding and Functions of the CyaA Toxin of Bordetella Pertussis, the Causative Agent of Whooping Cough. Biophysical Journal. 112(3). 523a–523a. 1 indexed citations
13.
Chaoul, Nada, et al.. (2015). Rapamycin Impairs Antitumor CD8+ T-cell Responses and Vaccine-Induced Tumor Eradication. Cancer Research. 75(16). 3279–3291. 48 indexed citations
14.
Gauliard, Emilie, et al.. (2015). Characterization of interactions between inclusion membrane proteins from Chlamydia trachomatis. Frontiers in Cellular and Infection Microbiology. 5. 13–13. 38 indexed citations
15.
Chenal, Alexandre, Johanna C. Karst, Anna Woźniak, et al.. (2010). Calcium-Induced Folding and Stabilization of the Intrinsically Disordered RTX Domain of the CyaA Toxin. Biophysical Journal. 99(11). 3744–3753. 59 indexed citations
17.
Berraondo, Pedro, et al.. (2007). Eradication of Large Tumors in Mice by a Tritherapy Targeting the Innate, Adaptive, and Regulatory Components of the Immune System. Cancer Research. 67(18). 8847–8855. 88 indexed citations
18.
Majlessi, Laleh, Marcela Simsova, Priscille Brodin, et al.. (2006). An Increase in Antimycobacterial Th1-Cell Responses by Prime-Boost Protocols of Immunization Does Not Enhance Protection against Tuberculosis. Infection and Immunity. 74(4). 2128–2137. 86 indexed citations
19.
Karimova, Gouzel, Agnès Ullmann, & Daniel Ladant. (2000). [5] A bacterial two-hybrid system that exploits a cAMP signaling cascade in Escherichia coli. Methods in enzymology on CD-ROM/Methods in enzymology. 328. 59–73. 128 indexed citations
20.
Ladant, Daniel & Gouzel Karimova. (2000). Genetic systems for analyzing protein–protein interactions in bacteria. Research in Microbiology. 151(9). 711–720. 23 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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