Doo Yeon Kim

6.8k total citations · 3 hit papers
56 papers, 4.9k citations indexed

About

Doo Yeon Kim is a scholar working on Molecular Biology, Physiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Doo Yeon Kim has authored 56 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 29 papers in Physiology and 14 papers in Cellular and Molecular Neuroscience. Recurrent topics in Doo Yeon Kim's work include Alzheimer's disease research and treatments (27 papers), Neuroinflammation and Neurodegeneration Mechanisms (9 papers) and Neuroscience and Neuropharmacology Research (8 papers). Doo Yeon Kim is often cited by papers focused on Alzheimer's disease research and treatments (27 papers), Neuroinflammation and Neurodegeneration Mechanisms (9 papers) and Neuroscience and Neuropharmacology Research (8 papers). Doo Yeon Kim collaborates with scholars based in United States, South Korea and Germany. Doo Yeon Kim's co-authors include Rudolph E. Tanzi, Se Hoon Choi, Carla D’Avanzo, Dora M. Kovacs, Dora M. Kovacs, Young Hye Kim, Laura Ingano, Enjana Bylykbashi, Matthias Hebisch and Can Zhang and has published in prestigious journals such as Nature, Science and Journal of Biological Chemistry.

In The Last Decade

Doo Yeon Kim

54 papers receiving 4.8k citations

Hit Papers

A three-dimensional human neural cell culture model of Al... 2014 2026 2018 2022 2014 2018 2018 250 500 750

Peers

Doo Yeon Kim
Wayne W. Poon United States
Brian J. Wainger United States
Nga Bien‐Ly United States
Lichuan Yang United States
Doo Yeon Kim
Citations per year, relative to Doo Yeon Kim Doo Yeon Kim (= 1×) peers Mathew Blurton‐Jones

Countries citing papers authored by Doo Yeon Kim

Since Specialization
Citations

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

Fields of papers citing papers by Doo Yeon Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Doo Yeon Kim. 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 Doo Yeon Kim. The network helps show where Doo Yeon Kim may publish in the future.

Co-authorship network of co-authors of Doo Yeon Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Doo Yeon Kim. A scholar is included among the top collaborators of Doo Yeon Kim 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 Doo Yeon Kim. Doo Yeon Kim 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
1.
Castanho, Isabel, Pourya Naderi Yeganeh, Carles A. Boix, et al.. (2025). Molecular hallmarks of excitatory and inhibitory neuronal resilience to Alzheimer’s disease. Molecular Neurodegeneration. 20(1). 103–103.
2.
Hebisch, Matthias, Katharina Wolf, Aldo R. Boccaccini, et al.. (2023). The Impact of the Cellular Environment and Aging on Modeling Alzheimer's Disease in 3D Cell Culture Models. Advanced Science. 10(8). e2205037–e2205037. 21 indexed citations
3.
Jorfi, Mehdi, Joseph Park, Chih‐Chung Lin, et al.. (2023). Infiltrating CD8+ T cells exacerbate Alzheimer’s disease pathology in a 3D human neuroimmune axis model. Nature Neuroscience. 26(9). 1489–1504. 91 indexed citations
4.
Washicosky, Kevin J., Djuna von Maydell, Susan Kim, et al.. (2020). Amyloid-β42/40 ratio drives tau pathology in 3D human neural cell culture models of Alzheimer’s disease. Nature Communications. 11(1). 1377–1377. 109 indexed citations
5.
Shin, Yoojin, Se Hoon Choi, Eunhee Kim, et al.. (2019). Blood–Brain Barrier Dysfunction in a 3D In Vitro Model of Alzheimer's Disease. Advanced Science. 6(20). 1900962–1900962. 222 indexed citations
6.
Zheng, Fang, Benedikt Zott, Carla D’Avanzo, et al.. (2018). β-Secretase BACE1 Promotes Surface Expression and Function of Kv3.4 at Hippocampal Mossy Fiber Synapses. Journal of Neuroscience. 38(14). 3480–3494. 15 indexed citations
7.
Kim, Young Hye, Kyuhwan Na, Doo Yeon Kim, et al.. (2018). Hydrogel-incorporating unit in a well: 3D cell culture for high-throughput analysis. Lab on a Chip. 18(17). 2604–2613. 22 indexed citations
8.
Choi, Se Hoon, Enjana Bylykbashi, Zena K. Chatila, et al.. (2018). Combined adult neurogenesis and BDNF mimic exercise effects on cognition in an Alzheimer’s mouse model. Science. 361(6406). 595 indexed citations breakdown →
9.
Chatila, Zena K., Eunhee Kim, Enjana Bylykbashi, et al.. (2018). BACE1 Regulates Proliferation and Neuronal Differentiation of Newborn Cells in the Adult Hippocampus in Mice. eNeuro. 5(4). ENEURO.0067–18.2018. 22 indexed citations
10.
Jorfi, Mehdi, Carla D’Avanzo, Rudolph E. Tanzi, Doo Yeon Kim, & Daniel Irimia. (2018). Human Neurospheroid Arrays for In Vitro Studies of Alzheimer’s Disease. Scientific Reports. 8(1). 2450–2450. 90 indexed citations
11.
Choi, Se Hoon, Young Hye Kim, Luisa Quinti, Rudolph E. Tanzi, & Doo Yeon Kim. (2016). 3D culture models of Alzheimer’s disease: a road map to a “cure-in-a-dish”. Molecular Neurodegeneration. 11(1). 75–75. 102 indexed citations
12.
Kim, Young Hye, Se Hoon Choi, Carla D’Avanzo, et al.. (2015). A 3D human neural cell culture system for modeling Alzheimer's disease. Nature Protocols. 10(7). 985–1006. 201 indexed citations
13.
D’Avanzo, Carla, et al.. (2014). BACE1 activity regulates cell surface contactin-2 levels. Molecular Neurodegeneration. 9(1). 4–4. 43 indexed citations
14.
Hutter‐Paier, Birgit, Henri J. Huttunen, Luigi Puglielli, et al.. (2010). The ACAT Inhibitor CP-113,818 Markedly Reduces Amyloid Pathology in a Mouse Model of Alzheimer's Disease. Neuron. 68(5). 1014–1014. 7 indexed citations
15.
Huttunen, Henri J., Suzanne Y. Guénette, Weiming Xia, et al.. (2007). HtrA2 Regulates β-Amyloid Precursor Protein (APP) Metabolism through Endoplasmic Reticulum-associated Degradation. Journal of Biological Chemistry. 282(38). 28285–28295. 59 indexed citations
16.
Kim, Doo Yeon, Bryce W. Carey, Haibin Wang, et al.. (2007). BACE1 regulates voltage-gated sodium channels and neuronal activity. Nature Cell Biology. 9(7). 755–764. 251 indexed citations
17.
Hutter‐Paier, Birgit, Henri J. Huttunen, Luigi Puglielli, et al.. (2004). The ACAT Inhibitor CP-113,818 Markedly Reduces Amyloid Pathology in a Mouse Model of Alzheimer's Disease. Neuron. 44(2). 227–238. 221 indexed citations
18.
Kim, Doo Yeon, Seok Joon Won, & Byoung Joo Gwag. (2002). Analysis of mitochondrial free radical generation in animal models of neuronal disease. Free Radical Biology and Medicine. 33(5). 715–723. 27 indexed citations
19.
Kim, Doo Yeon, et al.. (2001). High Abundance of GluR1 mRNA and Reduced Q/R Editing of GluR2 mRNA in Individual NADPH-Diaphorase Neurons. Molecular and Cellular Neuroscience. 17(6). 1025–1033. 18 indexed citations
20.
Kam, Yoonseok, Doo Yeon Kim, Soo Kyung Koo, & Cheol O. Joe. (1998). Transfer of second messengers through gap junction connexin 43 channels reconstituted in liposomes. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1372(2). 384–388. 48 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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