Mary‐Lee Dequéant

1.7k total citations
12 papers, 1.2k citations indexed

About

Mary‐Lee Dequéant is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Mary‐Lee Dequéant has authored 12 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Immunology. Recurrent topics in Mary‐Lee Dequéant's work include Developmental Biology and Gene Regulation (6 papers), Congenital heart defects research (5 papers) and CRISPR and Genetic Engineering (4 papers). Mary‐Lee Dequéant is often cited by papers focused on Developmental Biology and Gene Regulation (6 papers), Congenital heart defects research (5 papers) and CRISPR and Genetic Engineering (4 papers). Mary‐Lee Dequéant collaborates with scholars based in United States, France and Germany. Mary‐Lee Dequéant's co-authors include Olivier Pourquié, Earl Glynn, Arcady Mushegian, J. Kim Dale, Matthias Wahl, Jie Chen, Karin Gaudenz, Marta Maroto, Pascale Malapert and Mike J. McGrew and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Mary‐Lee Dequéant

12 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mary‐Lee Dequéant United States 7 1.0k 179 151 148 89 12 1.2k
Lea Goentoro United States 11 822 0.8× 147 0.8× 148 1.0× 77 0.5× 147 1.7× 17 1.2k
Ariel M. Pani United States 13 796 0.8× 143 0.8× 255 1.7× 73 0.5× 105 1.2× 26 1.3k
Miguel Maroto United Kingdom 17 1.1k 1.0× 186 1.0× 126 0.8× 100 0.7× 84 0.9× 22 1.2k
J. Kim Dale United Kingdom 20 1.8k 1.7× 343 1.9× 205 1.4× 157 1.1× 173 1.9× 35 2.0k
Michael P. Weir United States 18 1.1k 1.1× 313 1.7× 85 0.6× 177 1.2× 143 1.6× 38 1.2k
Peter Walentek Germany 17 805 0.8× 353 2.0× 151 1.0× 107 0.7× 86 1.0× 34 1.1k
Albert Erives United States 21 1.2k 1.2× 305 1.7× 120 0.8× 195 1.3× 161 1.8× 31 1.5k
Reiko Amikura Japan 18 1.1k 1.0× 305 1.7× 189 1.3× 171 1.2× 159 1.8× 29 1.4k
Aneesh Acharya United States 2 534 0.5× 90 0.5× 99 0.7× 50 0.3× 131 1.5× 3 790
J. Omar Yáñez-Cuna Austria 10 1.3k 1.3× 259 1.4× 70 0.5× 404 2.7× 172 1.9× 11 1.7k

Countries citing papers authored by Mary‐Lee Dequéant

Since Specialization
Citations

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

Fields of papers citing papers by Mary‐Lee Dequéant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mary‐Lee Dequéant. 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 Mary‐Lee Dequéant. The network helps show where Mary‐Lee Dequéant may publish in the future.

Co-authorship network of co-authors of Mary‐Lee Dequéant

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

All Works

12 of 12 papers shown
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Dequéant, Mary‐Lee, Jason Sagert, Hui Yu, et al.. (2021). Abstract 1537: CD70 knockout: A novel approach to augment CAR-T cell function. Cancer Research. 81(13_Supplement). 1537–1537. 4 indexed citations
4.
Pham, Minh Thu, et al.. (2020). Abstract 6595: Targeting T cell lymphomas with CRISPR/Cas9-generated anti-CD70 allogeneic CAR-T cells. Cancer Research. 80(16_Supplement). 6595–6595. 1 indexed citations
5.
Dequéant, Mary‐Lee, Delphine Fagegaltier, Yanhui Hu, et al.. (2015). Discovery of progenitor cell signatures by time-series synexpression analysis during Drosophila embryonic cell immortalization. Proceedings of the National Academy of Sciences. 112(42). 12974–12979. 24 indexed citations
6.
Roellig, Daniela, Mary‐Lee Dequéant, Olivier Tassy, et al.. (2011). Evolutionary plasticity of segmentation clock networks. Development. 138(13). 2783–2792. 148 indexed citations
7.
Roellig, Daniela, Mary‐Lee Dequéant, Olivier Tassy, et al.. (2009). 15-P018 A phase-ordered microarray screen for cyclic genes in zebrafish reveals her genes as the conserved core of the somitogenesis clock. Mechanisms of Development. 126. S252–S253. 2 indexed citations
8.
Dequéant, Mary‐Lee & Olivier Pourquié. (2008). Segmental patterning of the vertebrate embryonic axis. Nature Reviews Genetics. 9(5). 370–382. 293 indexed citations
9.
Dequéant, Mary‐Lee, Earl Glynn, Karin Gaudenz, et al.. (2006). A Complex Oscillating Network of Signaling Genes Underlies the Mouse Segmentation Clock. Science. 314(5805). 1595–1598. 342 indexed citations
10.
Dequéant, Mary‐Lee & Olivier Pourquié. (2005). Chicken genome: New tools and concepts. Developmental Dynamics. 232(4). 883–886. 13 indexed citations
11.
Maroto, Miguel, J. Kim Dale, Mary‐Lee Dequéant, Anne‐Cécile Petit, & Olivier Pourquié. (2005). Synchronised cycling gene oscillations in presomitic mesoderm cells require cell-cell contact. The International Journal of Developmental Biology. 49(2-3). 309–315. 75 indexed citations
12.
Dale, J. Kim, Marta Maroto, Mary‐Lee Dequéant, et al.. (2003). Periodic Notch inhibition by Lunatic Fringe underlies the chick segmentation clock. Nature. 421(6920). 275–278. 262 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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