Lan T.M. Dao

1.1k total citations · 1 hit paper
25 papers, 640 citations indexed

About

Lan T.M. Dao is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Lan T.M. Dao has authored 25 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 6 papers in Genetics and 5 papers in Surgery. Recurrent topics in Lan T.M. Dao's work include RNA Research and Splicing (7 papers), Genomics and Chromatin Dynamics (6 papers) and Mesenchymal stem cell research (6 papers). Lan T.M. Dao is often cited by papers focused on RNA Research and Splicing (7 papers), Genomics and Chromatin Dynamics (6 papers) and Mesenchymal stem cell research (6 papers). Lan T.M. Dao collaborates with scholars based in Vietnam, France and South Korea. Lan T.M. Dao's co-authors include Salvatore Spicuglia, Denis Puthier, Laurent Vanhille, Aurélien Griffon, Nicolas Fernandez, Mohamed Belhocine, Ève-Lyne Mathieu, Jean‐Christophe Andrau, Muhammad Ahmad Maqbool and Guillaume Charbonnier and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Nature Genetics.

In The Last Decade

Lan T.M. Dao

23 papers receiving 635 citations

Hit Papers

Modeling blood-brain barr... 2024 2026 2024 20 40 60
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Modeling blood-brain barrier formation and cerebral cavernous malformations in human PSC-derived organoids
    2024 66 citations Lan T.M. Dao, Lu Lu et al. Cell stem cell profile →

Author Peers

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

Author Last Decade Papers Cites
Lan T.M. Dao 461 129 84 55 46 25 640
Dekker C. Deacon 607 1.3× 80 0.6× 114 1.4× 21 0.4× 38 0.8× 18 734
Jinmi Choi 515 1.1× 91 0.7× 57 0.7× 38 0.7× 15 0.3× 17 590
Miriam Gagliardi 463 1.0× 165 1.3× 75 0.9× 49 0.9× 18 0.4× 18 564
Zoltán Simándi 320 0.7× 70 0.5× 42 0.5× 67 1.2× 21 0.5× 19 457
Guanyi Huang 361 0.8× 47 0.4× 93 1.1× 32 0.6× 33 0.7× 9 474
Soheila Sharghi-Namini 418 0.9× 183 1.4× 36 0.4× 40 0.7× 21 0.5× 9 547
Ita Costello 796 1.7× 60 0.5× 108 1.3× 43 0.8× 20 0.4× 18 898
Veronika Akopian 903 2.0× 53 0.4× 135 1.6× 30 0.5× 64 1.4× 9 968
Juliette Delhove 296 0.6× 79 0.6× 67 0.8× 24 0.4× 39 0.8× 24 484

Countries citing papers authored by Lan T.M. Dao

Since Specialization
Citations

This map shows the geographic impact of Lan T.M. Dao'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 Lan T.M. Dao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lan T.M. Dao more than expected).

Fields of papers citing papers by Lan T.M. Dao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lan T.M. Dao. 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 Lan T.M. Dao. The network helps show where Lan T.M. Dao may publish in the future.

Co-authorship network of co-authors of Lan T.M. Dao

This figure shows the co-authorship network connecting the top 25 collaborators of Lan T.M. Dao. A scholar is included among the top collaborators of Lan T.M. Dao 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 Lan T.M. Dao. Lan T.M. Dao 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
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Dao, Lan T.M., Lu Lu, Tianyang Xu, et al.. (2024). Modeling blood-brain barrier formation and cerebral cavernous malformations in human PSC-derived organoids. Cell stem cell. 31(6). 818–833.e11. 66 indexed citations breakdown →
3.
Wang, Chenran, et al.. (2024). Utilizing human cerebral organoids to model breast cancer brain metastasis in culture. Breast Cancer Research. 26(1). 108–108. 8 indexed citations
4.
Essen, Dominic van, Lan T.M. Dao, Guillaume Charbonnier, et al.. (2023). Short tandem repeats are important contributors to silencer elements in T cells. Nucleic Acids Research. 51(10). 4845–4866. 6 indexed citations
5.
Hoang, Duc M., Kien T. Nguyen, Van T. Hoang, et al.. (2021). Clinical Study of Mesenchymal Stem/Stromal Cell Therapy for the Treatment of Frailty: A Proposed Experimental Design for Therapeutic and Mechanistic Investigation. The Journals of Gerontology Series A. 77(7). 1287–1291. 3 indexed citations
6.
Souaid, Charbel, Himanshu Narayan Singh, Lan T.M. Dao, et al.. (2021). Epromoters function as a hub to recruit key transcription factors required for the inflammatory response. Nature Communications. 12(1). 6660–6660. 22 indexed citations
7.
Trân, Kien, et al.. (2021). Novel findings from family-based exome sequencing for children with biliary atresia. Scientific Reports. 11(1). 21815–21815. 9 indexed citations
8.
Molitor, Anne, Magali Torres, Lan T.M. Dao, et al.. (2020). Integration of high-throughput reporter assays identify a critical enhancer of the Ikzf1 gene. PLoS ONE. 15(5). e0233191–e0233191. 3 indexed citations
9.
Maqbool, Muhammad Ahmad, Amal Zine El Aabidine, Anne Molitor, et al.. (2020). Alternative Enhancer Usage and Targeted Polycomb Marking Hallmark Promoter Choice during T Cell Differentiation. Cell Reports. 32(7). 108048–108048. 13 indexed citations
10.
Vinh, Lê Sỹ, Hieu Nguyen, Lan T.M. Dao, et al.. (2020). Genetic landscape of autism spectrum disorder in Vietnamese children. Scientific Reports. 10(1). 5034–5034. 18 indexed citations
11.
Dao, Lan T.M., et al.. (2020). Imaging the urothelium with OCT. 4. 7–7.
12.
Dao, Lan T.M., Ève-Lyne Mathieu, Magali Torres, et al.. (2019). A critical regulator of Bcl2 revealed by systematic transcript discovery of lncRNAs associated with T-cell differentiation. Scientific Reports. 9(1). 4707–4707. 8 indexed citations
13.
Vinh, Lê Sỹ, et al.. (2019). A Vietnamese human genetic variation database. Human Mutation. 40(10). 1664–1675. 28 indexed citations
14.
Le, Duc‐Hau & Lan T.M. Dao. (2018). Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs. Journal of Molecular Biology. 430(15). 2219–2230. 16 indexed citations
15.
Dao, Lan T.M., Ariel Galindo‐Albarrán, Jaime A. Castro-Mondragón, et al.. (2017). Genome-wide characterization of mammalian promoters with distal enhancer functions. Nature Genetics. 49(7). 1073–1081. 167 indexed citations
16.
Vanhille, Laurent, Aurélien Griffon, Muhammad Ahmad Maqbool, et al.. (2015). High-throughput and quantitative assessment of enhancer activity in mammals by CapStarr-seq. Nature Communications. 6(1). 6905–6905. 107 indexed citations
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Mathieu, Ève-Lyne, Mohamed Belhocine, Lan T.M. Dao, Denis Puthier, & Salvatore Spicuglia. (2014). Rôle des longs ARN non codants dans le développement normal et pathologique. médecine/sciences. 30(8-9). 790–796. 75 indexed citations
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Jun, Hee‐Sook, Lan T.M. Dao, Jae‐Chul Pyun, & Sungbo Cho. (2013). Effect of cell senescence on the impedance measurement of adipose tissue-derived stem cells. Enzyme and Microbial Technology. 53(5). 302–306. 16 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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