Andrew S. Yoo

5.2k total citations · 1 hit paper
48 papers, 3.8k citations indexed

About

Andrew S. Yoo is a scholar working on Molecular Biology, Cancer Research and Cellular and Molecular Neuroscience. According to data from OpenAlex, Andrew S. Yoo has authored 48 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 15 papers in Cancer Research and 13 papers in Cellular and Molecular Neuroscience. Recurrent topics in Andrew S. Yoo's work include MicroRNA in disease regulation (15 papers), Pluripotent Stem Cells Research (12 papers) and RNA Interference and Gene Delivery (8 papers). Andrew S. Yoo is often cited by papers focused on MicroRNA in disease regulation (15 papers), Pluripotent Stem Cells Research (12 papers) and RNA Interference and Gene Delivery (8 papers). Andrew S. Yoo collaborates with scholars based in United States, Canada and United Kingdom. Andrew S. Yoo's co-authors include Robert H. Crabtree, Iva Greenwald, Alfred Xuyang Sun, Brett T. Staahl, Lei Chen, Matheus B. Victor, Aleksandr Shcheglovitov, Yulong Li, Richard W. Tsien and Thomas Portmann and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Andrew S. Yoo

48 papers receiving 3.8k citations

Hit Papers

MicroRNA-mediated convers... 2011 2026 2016 2021 2011 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew S. Yoo United States 28 2.9k 878 793 510 371 48 3.8k
Gioele La Manno Switzerland 19 5.1k 1.8× 1.2k 1.4× 919 1.2× 755 1.5× 691 1.9× 29 7.5k
James Smith United Kingdom 17 1.9k 0.7× 530 0.6× 497 0.6× 523 1.0× 455 1.2× 22 2.9k
Tracy L. Young‐Pearse United States 35 2.8k 1.0× 1.0k 1.2× 588 0.7× 364 0.7× 1.5k 4.0× 82 4.4k
Gonçalo Castelo‐Branco Sweden 35 4.4k 1.5× 1.4k 1.6× 912 1.2× 1.5k 3.0× 373 1.0× 52 6.8k
Jacinta Lucero United States 22 1.8k 0.6× 567 0.6× 523 0.7× 124 0.2× 445 1.2× 25 3.4k
Qiaolin Deng Sweden 28 4.2k 1.5× 648 0.7× 1.0k 1.3× 267 0.5× 144 0.4× 56 5.5k
Philipp Koch Germany 33 2.9k 1.0× 1.2k 1.4× 200 0.3× 1.0k 2.0× 545 1.5× 75 4.2k
Joshua J. Breunig United States 26 2.1k 0.7× 821 0.9× 345 0.4× 886 1.7× 436 1.2× 56 3.5k
Qin Shen China 26 3.6k 1.3× 1.4k 1.6× 1.0k 1.3× 2.5k 5.0× 202 0.5× 81 5.9k
Matthew H. Bailey United States 25 3.1k 1.1× 924 1.1× 404 0.5× 1.3k 2.5× 1.5k 4.0× 35 6.3k

Countries citing papers authored by Andrew S. Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Andrew S. Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew S. Yoo. 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 Andrew S. Yoo. The network helps show where Andrew S. Yoo may publish in the future.

Co-authorship network of co-authors of Andrew S. Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew S. Yoo. A scholar is included among the top collaborators of Andrew S. Yoo 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 Andrew S. Yoo. Andrew S. Yoo 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.
Cates, K. Lynn, et al.. (2025). Fate erasure logic of gene networks underlying direct neuronal conversion of somatic cells by microRNAs. Cell Reports. 44(1). 115153–115153. 1 indexed citations
2.
Wu, Shanyun, et al.. (2024). Notch inhibition enhances morphological reprogramming of microRNA-induced human neurons. Stem Cells. 43(2). 1 indexed citations
3.
4.
Sato, Chihiro, Elena Ficulle, Anan Yu, et al.. (2022). Recapitulation of endogenous 4R tau expression and formation of insoluble tau in directly reprogrammed human neurons. Cell stem cell. 29(6). 918–932.e8. 29 indexed citations
5.
Liu, Yangjian, et al.. (2021). MiR-124 synergism with ELAVL3 enhances target gene expression to promote neuronal maturity. Proceedings of the National Academy of Sciences. 118(22). 19 indexed citations
6.
Sato, Chihiro, Elena Ficulle, Anan Yu, et al.. (2021). Recapitulation of Endogenous 4R Tau Expression and Formation of Insoluble Tau in Directly Reprogrammed Human Neurons. SSRN Electronic Journal. 5 indexed citations
7.
8.
Ishikawa, Mitsuru, Takeshi Aoyama, Takefumi Sone, et al.. (2020). miRNA-Based Rapid Differentiation of Purified Neurons from hPSCs Advancestowards Quick Screening for Neuronal Disease Phenotypes In Vitro. Cells. 9(3). 532–532. 28 indexed citations
9.
Franco, Antonietta, Barbara Zabłocka, Cindy V. Ly, et al.. (2020). Burst mitofusin activation reverses neuromuscular dysfunction in murine CMT2A. eLife. 9. 42 indexed citations
10.
Gontarz, Paul, Shuhua Fu, Xiaoyun Xing, et al.. (2020). Comparison of differential accessibility analysis strategies for ATAC-seq data. Scientific Reports. 10(1). 10150–10150. 34 indexed citations
11.
Cates, K. Lynn, Matthew J. McCoy, Yangjian Liu, et al.. (2020). Deconstructing Stepwise Fate Conversion of Human Fibroblasts to Neurons by MicroRNAs. Cell stem cell. 28(1). 127–140.e9. 41 indexed citations
12.
McCoy, Matthew J., K. Lynn Cates, Yangjian Liu, et al.. (2019). Deconstructing Stepwise Fate Conversion of Human Fibroblasts to Neurons by MicroRNAs. SSRN Electronic Journal. 1 indexed citations
13.
Lee, Seong Won, et al.. (2018). MicroRNAs Overcome Cell Fate Barrier by Reducing EZH2-Controlled REST Stability during Neuronal Conversion of Human Adult Fibroblasts. Developmental Cell. 46(1). 73–84.e7. 55 indexed citations
14.
Victor, Matheus B., Michelle Richner, Tracey O. Hermanstyne, et al.. (2014). Generation of Human Striatal Neurons by MicroRNA-Dependent Direct Conversion of Fibroblasts. Neuron. 84(2). 311–323. 227 indexed citations
15.
Yoo, Andrew S., Alfred Xuyang Sun, Li Li, et al.. (2011). MicroRNA-mediated conversion of human fibroblasts to neurons. Nature. 476(7359). 228–231. 778 indexed citations breakdown →
16.
Yoo, Andrew S., Brett T. Staahl, Lei Chen, & Robert H. Crabtree. (2009). MicroRNA-mediated switching of chromatin-remodelling complexes in neural development. Nature. 460(7255). 642–646. 485 indexed citations
17.
Yoo, Andrew S. & Iva Greenwald. (2005). LIN-12/Notch Activation Leads to MicroRNA-Mediated Down-Regulation of Vav in C. elegans. Science. 310(5752). 1330–1333. 121 indexed citations
18.
Yoo, Andrew S., Carlos Bais, & Iva Greenwald. (2004). Crosstalk Between the EGFR and LIN-12/Notch Pathways in C. elegans Vulval Development. Science. 303(5658). 663–666. 214 indexed citations
19.
Yoo, Andrew S., et al.. (1999). Process extension and intracellular Ca2+ in cultured murine oligodendrocytes. Brain Research. 827(1-2). 19–27. 28 indexed citations
20.
Yoo, Andrew S., Jennifer Harris, & B. Dubrovsky. (1996). Dose–Response Study of Dehydroepiandrosterone Sulfate on Dentate Gyrus Long Term Potentiation. Experimental Neurology. 137(1). 151–156. 58 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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