Yu‐Ting L. Dingle

436 total citations
8 papers, 338 citations indexed

About

Yu‐Ting L. Dingle is a scholar working on Cellular and Molecular Neuroscience, Biomedical Engineering and Molecular Biology. According to data from OpenAlex, Yu‐Ting L. Dingle has authored 8 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Cellular and Molecular Neuroscience, 4 papers in Biomedical Engineering and 3 papers in Molecular Biology. Recurrent topics in Yu‐Ting L. Dingle's work include 3D Printing in Biomedical Research (4 papers), Neuroscience and Neural Engineering (3 papers) and Nanoparticle-Based Drug Delivery (2 papers). Yu‐Ting L. Dingle is often cited by papers focused on 3D Printing in Biomedical Research (4 papers), Neuroscience and Neural Engineering (3 papers) and Nanoparticle-Based Drug Delivery (2 papers). Yu‐Ting L. Dingle collaborates with scholars based in United States. Yu‐Ting L. Dingle's co-authors include David L. Kaplan, Thomas J.F. Nieland, Edith Mathiowitz, Daniel Cho, Joshua Reineke, Michael L. Lovett, Diane Hoffman–Kim, A Morelló, Christopher G. Thanos and Jules S. Jacob and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Functional Materials and Journal of Controlled Release.

In The Last Decade

Yu‐Ting L. Dingle

8 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yu‐Ting L. Dingle United States	7	137	103	93	63	46	8	338
Martina Giannaccini Italy	9	144 1.1×	130 1.3×	126 1.4×	31 0.5×	107 2.3×	21	421
Ulrica Englund Johansson Sweden	8	115 0.8×	86 0.8×	117 1.3×	13 0.2×	60 1.3×	13	357
Farrah S. Mohammed United States	7	148 1.1×	102 1.0×	89 1.0×	17 0.3×	81 1.8×	7	389
Fengshi Zhang China	11	120 0.9×	158 1.5×	73 0.8×	18 0.3×	148 3.2×	25	383
Bhav Harshad Parikh Singapore	14	91 0.7×	44 0.4×	283 3.0×	46 0.7×	119 2.6×	21	677
Sang-Myung Jung South Korea	10	85 0.6×	32 0.3×	52 0.6×	37 0.6×	153 3.3×	16	338
M. P. Valikhov Russia	12	101 0.7×	76 0.7×	133 1.4×	37 0.6×	89 1.9×	36	423
Delaney G. Fisher United States	8	125 0.9×	28 0.3×	87 0.9×	9 0.1×	36 0.8×	12	311
Keng‐Yen Fu Taiwan	11	83 0.6×	54 0.5×	42 0.5×	11 0.2×	122 2.7×	18	354

Countries citing papers authored by Yu‐Ting L. Dingle

Since Specialization

Citations

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

Fields of papers citing papers by Yu‐Ting L. Dingle

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu‐Ting L. Dingle. 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 Yu‐Ting L. Dingle. The network helps show where Yu‐Ting L. Dingle may publish in the future.

Co-authorship network of co-authors of Yu‐Ting L. Dingle

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

All Works

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8 of 8 papers shown

Dingle, Yu‐Ting L., et al.. (2021). Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture. STAR Protocols. 2(1). 100292–100292. 9 indexed citations

Dingle, Yu‐Ting L., et al.. (2020). Functional Characterization of Three-Dimensional Cortical Cultures for In Vitro Modeling of Brain Networks. iScience. 23(8). 101434–101434. 28 indexed citations

Lovett, Michael L., Thomas J.F. Nieland, Yu‐Ting L. Dingle, & David L. Kaplan. (2020). Innovations in 3D Tissue Models of Human Brain Physiology and Diseases. Advanced Functional Materials. 30(44). 64 indexed citations

Dingle, Yu‐Ting L., Molly E. Boutin, Anda M. Chirila, et al.. (2015). Three-Dimensional Neural Spheroid Culture: An In Vitro Model for Cortical Studies. Tissue Engineering Part C Methods. 21(12). 1274–1283. 98 indexed citations

Dingle, Yu‐Ting L., Molly E. Boutin, Anda M. Chirila, et al.. (2015). 3D Neural Spheroid Culture: An In Vitro Model for Cortical Studies. 1 indexed citations

Reineke, Joshua, Daniel Cho, Yu‐Ting L. Dingle, et al.. (2013). Unique insights into the intestinal absorption, transit, and subsequent biodistribution of polymer-derived microspheres. Proceedings of the National Academy of Sciences. 110(34). 13803–13808. 84 indexed citations

Mitchel, Jennifer A., et al.. (2013). Navigating neurites utilize cellular topography of Schwann cell somas and processes for optimal guidance. Acta Biomaterialia. 9(7). 7158–7168. 13 indexed citations

Reineke, Joshua, Daniel Cho, Yu‐Ting L. Dingle, et al.. (2013). Can bioadhesive nanoparticles allow for more effective particle uptake from the small intestine?. Journal of Controlled Release. 170(3). 477–484. 41 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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