Yejing Ge

2.8k total citations
27 papers, 2.1k citations indexed

About

Yejing Ge is a scholar working on Molecular Biology, Rehabilitation and Cancer Research. According to data from OpenAlex, Yejing Ge has authored 27 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 7 papers in Rehabilitation and 6 papers in Cancer Research. Recurrent topics in Yejing Ge's work include Muscle Physiology and Disorders (10 papers), MicroRNA in disease regulation (6 papers) and Hair Growth and Disorders (5 papers). Yejing Ge is often cited by papers focused on Muscle Physiology and Disorders (10 papers), MicroRNA in disease regulation (6 papers) and Hair Growth and Disorders (5 papers). Yejing Ge collaborates with scholars based in United States, Israel and South Korea. Yejing Ge's co-authors include Jie Chen, Elaine Fuchs, Yuting Sun, Hanseul Yang, Rene C. Adam, Nicholas C. Gomez, Zhong L. Hua, Lisa Polak, Maria Nikolova and Olivier Elemento and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Yejing Ge

27 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yejing Ge United States 20 1.4k 548 422 274 258 27 2.1k
Daisuke Nanba Japan 22 1.0k 0.7× 217 0.4× 420 1.0× 560 2.0× 170 0.7× 48 2.1k
Hanseul Yang United States 17 1.1k 0.8× 301 0.5× 341 0.8× 787 2.9× 324 1.3× 21 2.2k
Mỹ G. Mahoney United States 30 1.4k 1.0× 234 0.4× 633 1.5× 276 1.0× 278 1.1× 68 3.2k
Nicole Stokes United States 17 1.9k 1.3× 307 0.6× 702 1.7× 335 1.2× 930 3.6× 20 3.0k
Wen‐Hui Lien United States 19 1.7k 1.2× 187 0.3× 834 2.0× 235 0.9× 390 1.5× 24 2.5k
Bradley J. Merrill United States 26 2.7k 1.9× 225 0.4× 410 1.0× 324 1.2× 447 1.7× 41 3.3k
Andrey A. Sharov United States 27 1.1k 0.8× 304 0.6× 614 1.5× 271 1.0× 942 3.7× 40 2.2k
Anna Maria Lena Italy 26 2.0k 1.4× 1.2k 2.1× 195 0.5× 800 2.9× 105 0.4× 50 2.7k

Countries citing papers authored by Yejing Ge

Since Specialization
Citations

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

Fields of papers citing papers by Yejing Ge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yejing Ge

This figure shows the co-authorship network connecting the top 25 collaborators of Yejing Ge. A scholar is included among the top collaborators of Yejing Ge 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 Yejing Ge. Yejing Ge 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.
McAndrews, Kathleen M., Toru Miyake, Ehsan A. Ehsanipour, et al.. (2022). Dermal αSMA + myofibroblasts orchestrate skin wound repair via β1 integrin and independent of type I collagen production. The EMBO Journal. 41(7). e109470–e109470. 54 indexed citations
2.
Ge, Yejing, et al.. (2022). Toward Elucidating Epigenetic and Metabolic Regulation of Stem Cell Lineage Plasticity in Skin Aging. Frontiers in Cell and Developmental Biology. 10. 903904–903904. 6 indexed citations
3.
Baksh, Sanjeethan C., Shiri Gur‐Cohen, Brian Hurwitz, et al.. (2020). Extracellular serine controls epidermal stem cell fate and tumour initiation. Nature Cell Biology. 22(7). 779–790. 82 indexed citations
4.
Adam, Rene C., Hanseul Yang, Yejing Ge, et al.. (2020). NFI transcription factors provide chromatin access to maintain stem cell identity while preventing unintended lineage fate choices. Nature Cell Biology. 22(6). 640–650. 59 indexed citations
5.
Ellis, Stephanie J., Nicholas C. Gomez, John M. Levorse, et al.. (2019). Distinct modes of cell competition shape mammalian tissue morphogenesis. Nature. 569(7757). 497–502. 102 indexed citations
6.
Wang, Guan, et al.. (2019). Unraveling cancer lineage drivers in squamous cell carcinomas. Pharmacology & Therapeutics. 206. 107448–107448. 18 indexed citations
7.
Adam, Rene C., Hanseul Yang, Yejing Ge, et al.. (2018). Temporal Layering of Signaling Effectors Drives Chromatin Remodeling during Hair Follicle Stem Cell Lineage Progression. Cell stem cell. 22(3). 398–413.e7. 74 indexed citations
8.
Ge, Yejing & Elaine Fuchs. (2018). Stretching the limits: from homeostasis to stem cell plasticity in wound healing and cancer. Nature Reviews Genetics. 19(5). 311–325. 117 indexed citations
9.
Ge, Yejing, Nicholas C. Gomez, Rene C. Adam, et al.. (2017). Stem Cell Lineage Infidelity Drives Wound Repair and Cancer. Cell. 169(4). 636–650.e14. 238 indexed citations
10.
Yang, Hanseul, Rene C. Adam, Yejing Ge, Zhong L. Hua, & Elaine Fuchs. (2017). Epithelial-Mesenchymal Micro-niches Govern Stem Cell Lineage Choices. Cell. 169(3). 483–496.e13. 193 indexed citations
11.
Ge, Yejing, Liang Zhang, Maria Nikolova, Boris Reva, & Elaine Fuchs. (2015). Strand-specific in vivo screen of cancer-associated miRNAs unveils a role for miR-21∗ in SCC progression. Nature Cell Biology. 18(1). 111–121. 50 indexed citations
12.
Zhang, Liang, Yejing Ge, & Elaine Fuchs. (2014). miR-125b can enhance skin tumor initiation and promote malignant progression by repressing differentiation and prolonging cell survival. Genes & Development. 28(22). 2532–2546. 53 indexed citations
13.
Ge, Yejing, et al.. (2014). MicroRNA-146b Promotes Myogenic Differentiation and Modulates Multiple Gene Targets in Muscle Cells. PLoS ONE. 9(6). e100657–e100657. 44 indexed citations
14.
Ge, Yejing, et al.. (2013). Flt3L is a novel regulator of skeletal myogenesis. Journal of Cell Science. 126(Pt 15). 3370–9. 16 indexed citations
15.
Ge, Yejing & Jie Chen. (2012). Mammalian Target of Rapamycin (mTOR) Signaling Network in Skeletal Myogenesis. Journal of Biological Chemistry. 287(52). 43928–43935. 94 indexed citations
16.
Ge, Yejing, Mee‐Sup Yoon, & Jie Chen. (2011). Raptor and Rheb Negatively Regulate Skeletal Myogenesis through Suppression of Insulin Receptor Substrate 1 (IRS1). Journal of Biological Chemistry. 286(41). 35675–35682. 30 indexed citations
17.
Ge, Yejing & Jie Chen. (2011). MicroRNAs in skeletal myogenesis. Cell Cycle. 10(3). 441–448. 128 indexed citations
18.
Sun, Yuting, Yejing Ge, Jenny Drnevich, et al.. (2010). Mammalian target of rapamycin regulates miRNA-1 and follistatin in skeletal myogenesis. The Journal of Cell Biology. 189(7). 1157–1169. 164 indexed citations
19.
Goodman, Craig A., John W. Frey, Danielle Mabrey, et al.. (2010). A Phosphatidylinositol 3-Kinase/Protein Kinase B-independent Activation of Mammalian Target of Rapamycin Signaling Is Sufficient to Induce Skeletal Muscle Hypertrophy. Molecular Biology of the Cell. 21(18). 3258–3268. 97 indexed citations
20.
Goodman, Craig A., John W. Frey, Danielle Mabrey, et al.. (2010). A PI3K/PKB-Independent Activation of mTOR Signaling is Sufficient to Induce Skeletal Muscle Hypertrophy. Medicine & Science in Sports & Exercise. 42(10). 7–7. 1 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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