Michelle Dang

472 total citations
10 papers, 301 citations indexed

About

Michelle Dang is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Michelle Dang has authored 10 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Cell Biology and 3 papers in Oncology. Recurrent topics in Michelle Dang's work include Zebrafish Biomedical Research Applications (4 papers), Cell Adhesion Molecules Research (3 papers) and Peptidase Inhibition and Analysis (2 papers). Michelle Dang is often cited by papers focused on Zebrafish Biomedical Research Applications (4 papers), Cell Adhesion Molecules Research (3 papers) and Peptidase Inhibition and Analysis (2 papers). Michelle Dang collaborates with scholars based in United States, Germany and France. Michelle Dang's co-authors include Leonard I. Zon, Levi A. Garraway, Rachel E. Henderson, Harvey F. Lodish, Andreas Herrlich, Monika Hartmann, Rachel Fogley, Vivien J. Coulson‐Thomas, Mingxia Sun and John M. Gansner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Genetics.

In The Last Decade

Michelle Dang

10 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michelle Dang United States 9 161 104 67 46 33 10 301
Perry M. Chan Singapore 10 264 1.6× 106 1.0× 84 1.3× 69 1.5× 31 0.9× 14 461
Maren von der Ohe Germany 9 180 1.1× 49 0.5× 40 0.6× 108 2.3× 20 0.6× 10 341
Yelena Pavlova United States 11 437 2.7× 127 1.2× 107 1.6× 109 2.4× 22 0.7× 16 628
Priscilla Soo Australia 7 114 0.7× 62 0.6× 78 1.2× 140 3.0× 12 0.4× 9 311
Margarida Sancho United Kingdom 4 300 1.9× 143 1.4× 79 1.2× 54 1.2× 7 0.2× 5 439
Franck Coumailleau France 6 271 1.7× 148 1.4× 33 0.5× 36 0.8× 15 0.5× 9 362
Edward J. Davey Sweden 9 270 1.7× 56 0.5× 66 1.0× 65 1.4× 15 0.5× 10 388
М. В. Шепелев Russia 10 311 1.9× 79 0.8× 83 1.2× 27 0.6× 5 0.2× 32 412
Kossay Zaoui Canada 8 235 1.5× 161 1.5× 67 1.0× 31 0.7× 14 0.4× 13 369
Amanda L. Neisch United States 6 215 1.3× 184 1.8× 38 0.6× 64 1.4× 7 0.2× 9 439

Countries citing papers authored by Michelle Dang

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelle Dang

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

All Works

10 of 10 papers shown
1.
Ablain, Julien, Harriet Rothschild, Song Yang, et al.. (2022). Loss of NECTIN1 triggers melanoma dissemination upon local IGF1 depletion. Nature Genetics. 54(12). 1839–1852. 10 indexed citations
2.
Fazio, Maurizio, Ellen van Rooijen, Michelle Dang, et al.. (2021). SATB2 induction of a neural crest mesenchyme-like program drives melanoma invasion and drug resistance. eLife. 10. 9 indexed citations
3.
Sun, Mingxia, et al.. (2020). Meibomian Gland Dysfunction: What Have Animal Models Taught Us?. International Journal of Molecular Sciences. 21(22). 8822–8822. 33 indexed citations
4.
McConnell, Alicia M., Jeffrey K. Mito, Julien Ablain, et al.. (2018). Neural crest state activation in NRAS driven melanoma, but not in NRAS-driven melanocyte expansion. Developmental Biology. 449(2). 107–114. 16 indexed citations
5.
Dang, Michelle. (2018). A Summary of Newer and Safer Opioid Formulations. Current anesthesiology reports. 8(4). 337–341. 1 indexed citations
6.
Dang, Michelle, Rachel E. Henderson, Levi A. Garraway, & Leonard I. Zon. (2016). Long-term drug administration in the adult zebrafish using oral gavage for cancer preclinical studies. Disease Models & Mechanisms. 9(7). 811–20. 65 indexed citations
7.
Gansner, John M., et al.. (2016). Transplantation in zebrafish. Methods in cell biology. 138. 629–647. 26 indexed citations
8.
Dang, Michelle, Rachel Fogley, & Leonard I. Zon. (2016). Identifying Novel Cancer Therapies Using Chemical Genetics and Zebrafish. Advances in experimental medicine and biology. 916. 103–124. 32 indexed citations
9.
Dang, Michelle, Nicole Armbruster, Miles A. Miller, et al.. (2013). Regulated ADAM17-dependent EGF family ligand release by substrate-selecting signaling pathways. Proceedings of the National Academy of Sciences. 110(24). 9776–9781. 68 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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