Mai T. Ngo

429 total citations
12 papers, 286 citations indexed

About

Mai T. Ngo is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Mai T. Ngo has authored 12 papers receiving a total of 286 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Biomedical Engineering and 5 papers in Genetics. Recurrent topics in Mai T. Ngo's work include 3D Printing in Biomedical Research (5 papers), Glioma Diagnosis and Treatment (4 papers) and Angiogenesis and VEGF in Cancer (3 papers). Mai T. Ngo is often cited by papers focused on 3D Printing in Biomedical Research (5 papers), Glioma Diagnosis and Treatment (4 papers) and Angiogenesis and VEGF in Cancer (3 papers). Mai T. Ngo collaborates with scholars based in United States, United Kingdom and Vietnam. Mai T. Ngo's co-authors include Brendan A.C. Harley, Jann N. Sarkaria, Aidan E. Gilchrist, Marley J. Dewey, Bhushan Mahadik, Cong T. Nguyen, Juliann B. Tefft, Christopher S. Chen, Roger Oria and Jeroen Eyckmans and has published in prestigious journals such as Nature Cell Biology, Biomaterials and Advanced Functional Materials.

In The Last Decade

Mai T. Ngo

11 papers receiving 284 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mai T. Ngo United States 9 136 81 66 64 52 12 286
Arshia Ehsanipour United States 10 190 1.4× 65 0.8× 89 1.3× 115 1.8× 89 1.7× 11 469
Lionel Faivre France 10 71 0.5× 55 0.7× 52 0.8× 76 1.2× 41 0.8× 22 275
Lin Gao United States 9 95 0.7× 73 0.9× 40 0.6× 136 2.1× 39 0.8× 16 409
Marina Trouillas France 13 70 0.5× 101 1.2× 60 0.9× 189 3.0× 48 0.9× 21 421
Hengyi Wang China 13 73 0.5× 45 0.6× 54 0.8× 104 1.6× 56 1.1× 23 371
Stefan Stich Germany 13 89 0.7× 152 1.9× 38 0.6× 107 1.7× 54 1.0× 16 408
Anna Yakimova Russia 10 82 0.6× 62 0.8× 50 0.8× 164 2.6× 71 1.4× 25 398
Anna Blois Norway 10 114 0.8× 88 1.1× 90 1.4× 252 3.9× 52 1.0× 14 459
Milos Marinkovic United States 10 103 0.8× 180 2.2× 83 1.3× 103 1.6× 37 0.7× 14 404
Zhihu Qu China 5 74 0.5× 53 0.7× 55 0.8× 148 2.3× 58 1.1× 5 316

Countries citing papers authored by Mai T. Ngo

Since Specialization
Citations

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

Fields of papers citing papers by Mai T. Ngo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mai T. Ngo. 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 Mai T. Ngo. The network helps show where Mai T. Ngo may publish in the future.

Co-authorship network of co-authors of Mai T. Ngo

This figure shows the co-authorship network connecting the top 25 collaborators of Mai T. Ngo. A scholar is included among the top collaborators of Mai T. Ngo 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 Mai T. Ngo. Mai T. Ngo 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
1.
Jenison, Steven, et al.. (2025). -Omics approaches to study and model cell-cell interactions in engineered tissues. Frontiers in Chemical Engineering. 7. 1 indexed citations
2.
Uroz, Marina, Amy E. Stoddard, Bryan P. Sutherland, et al.. (2024). Differential stiffness between brain vasculature and parenchyma promotes metastatic infiltration through vessel co-option. Nature Cell Biology. 26(12). 2144–2153. 7 indexed citations
3.
Ngo, Mai T., Jann N. Sarkaria, & Brendan A.C. Harley. (2022). Perivascular Stromal Cells Instruct Glioblastoma Invasion, Proliferation, and Therapeutic Response within an Engineered Brain Perivascular Niche Model. Advanced Science. 9(31). e2201888–e2201888. 20 indexed citations
4.
Ngo, Mai T. & Brendan A.C. Harley. (2021). Progress in mimicking brain microenvironments to understand and treat neurological disorders. APL Bioengineering. 5(2). 20902–20902. 13 indexed citations
6.
Ngo, Mai T., et al.. (2021). Hydrogels Containing Gradients in Vascular Density Reveal Dose‐Dependent Role of Angiocrine Cues on Stem Cell Behavior. Advanced Functional Materials. 31(51). 13 indexed citations
7.
Gilchrist, Aidan E., et al.. (2021). Encapsulation of murine hematopoietic stem and progenitor cells in a thiol-crosslinked maleimide-functionalized gelatin hydrogel. Acta Biomaterialia. 131. 138–148. 34 indexed citations
9.
Ngo, Mai T. & Brendan A.C. Harley. (2020). Angiogenic biomaterials to promote therapeutic regeneration and investigate disease progression. Biomaterials. 255. 120207–120207. 52 indexed citations
10.
Ngo, Mai T. & Brendan A.C. Harley. (2018). Perivascular signals alter global gene expression profile of glioblastoma and response to temozolomide in a gelatin hydrogel. Biomaterials. 198. 122–134. 50 indexed citations
11.
Ngo, Mai T. & Brendan A.C. Harley. (2017). The Influence of Hyaluronic Acid and Glioblastoma Cell Coculture on the Formation of Endothelial Cell Networks in Gelatin Hydrogels. Advanced Healthcare Materials. 6(22). 55 indexed citations
12.
Ngo, Mai T., et al.. (2017). Chronic exposure of μg/L range Bisphenol A to adult zebrafish (Danio rerio) leading to adipogenesis. AIP conference proceedings. 1878. 20028–20028. 5 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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