Caifu Chen

10.0k total citations · 3 hit papers
38 papers, 6.2k citations indexed

About

Caifu Chen is a scholar working on Molecular Biology, Cancer Research and Plant Science. According to data from OpenAlex, Caifu Chen has authored 38 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 23 papers in Cancer Research and 7 papers in Plant Science. Recurrent topics in Caifu Chen's work include MicroRNA in disease regulation (18 papers), Molecular Biology Techniques and Applications (9 papers) and CRISPR and Genetic Engineering (8 papers). Caifu Chen is often cited by papers focused on MicroRNA in disease regulation (18 papers), Molecular Biology Techniques and Applications (9 papers) and CRISPR and Genetic Engineering (8 papers). Caifu Chen collaborates with scholars based in United States, Norway and China. Caifu Chen's co-authors include Dana Ridzon, Yu Liang, Linda Wong, Gregory J. Hannon, Lin He, Xingyue He, Zhenyu Xuan, Wen Xue, Michele A. Cleary and Aimee L. Jackson and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Caifu Chen

38 papers receiving 6.1k citations

Hit Papers

A microRNA component of the p53 tumour suppressor network 2007 2026 2013 2019 2007 2007 2007 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Caifu Chen United States 26 5.2k 4.2k 439 410 296 38 6.2k
Minju Ha South Korea 13 6.4k 1.2× 4.7k 1.1× 334 0.8× 242 0.6× 475 1.6× 16 7.6k
Chanseok Shin South Korea 27 5.9k 1.1× 4.2k 1.0× 784 1.8× 203 0.5× 521 1.8× 61 7.3k
Mo‐Fang Liu China 36 5.4k 1.0× 3.4k 0.8× 830 1.9× 459 1.1× 539 1.8× 73 6.6k
Ulf Andersson Ørom Denmark 25 5.2k 1.0× 4.1k 1.0× 265 0.6× 193 0.5× 293 1.0× 41 6.0k
Ahmad M. Khalil United States 27 6.8k 1.3× 5.9k 1.4× 323 0.7× 272 0.7× 249 0.8× 96 8.1k
Philip W. Garrett-Engele United States 14 8.6k 1.7× 6.0k 1.4× 450 1.0× 288 0.7× 578 2.0× 15 10.0k
Yong Sun Lee South Korea 29 5.1k 1.0× 3.7k 0.9× 146 0.3× 252 0.6× 312 1.1× 56 6.0k
Daehyun Baek South Korea 20 4.7k 0.9× 4.0k 1.0× 196 0.4× 208 0.5× 589 2.0× 35 5.9k
Vikram Agarwal United States 14 5.3k 1.0× 4.1k 1.0× 191 0.4× 212 0.5× 518 1.8× 21 6.6k
Yoontae Lee South Korea 22 6.9k 1.3× 5.3k 1.3× 1.0k 2.3× 222 0.5× 612 2.1× 38 8.3k

Countries citing papers authored by Caifu Chen

Since Specialization
Citations

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

Fields of papers citing papers by Caifu Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Caifu Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Caifu Chen. A scholar is included among the top collaborators of Caifu Chen 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 Caifu Chen. Caifu Chen 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.
Shen, Ningjia, Bin Zhu, Wei Zhang, et al.. (2022). Comprehensive Evaluation and Application of a Novel Method to Isolate Cell-Free DNA Derived From Bile of Biliary Tract Cancer Patients. Frontiers in Oncology. 12. 891917–891917. 7 indexed citations
2.
Peng, Hao, Rong Huang, Kui Wang, et al.. (2020). Development and Validation of an RNA Sequencing Assay for Gene Fusion Detection in Formalin-Fixed, Paraffin-Embedded Tumors. Journal of Molecular Diagnostics. 23(2). 223–233. 8 indexed citations
3.
Wang, Shuang, et al.. (2019). Combination of Point-Cloud Model and FCN for Dam Crack Detection and Scale Calculation. 5859–5862. 2 indexed citations
4.
Choi, Yong Jin, Chao‐Po Lin, Davide Risso, et al.. (2017). Deficiency of microRNA miR-34a expands cell fate potential in pluripotent stem cells. Science. 355(6325). 119 indexed citations
5.
Hurley, James, et al.. (2011). Stem-Loop RT-qPCR for MicroRNA Expression Profiling. Methods in molecular biology. 822. 33–52. 37 indexed citations
6.
Haase, Astrid D., Silvia Fenoglio, Felix Muerdter, et al.. (2010). Probing the initiation and effector phases of the somatic piRNA pathway inDrosophila. Genes & Development. 24(22). 2499–2504. 120 indexed citations
7.
Chen, Caifu, et al.. (2010). Quantitation of MicroRNAs by Real-Time RT-qPCR. Methods in molecular biology. 687. 113–134. 126 indexed citations
8.
Russell, I., et al.. (2009). Gene Expression in Stem Cells. Critical Reviews in Eukaryotic Gene Expression. 19(4). 289–300. 9 indexed citations
9.
Cheng, Angie, Mu Li, Yu Wang, et al.. (2009). Stem-Loop RT-PCR Quantification of siRNAs In Vitro and In Vivo. Oligonucleotides. 19(2). 203–208. 38 indexed citations
10.
Mestdagh, Pieter, Tom Feys, Nathalie Bernard‐Marissal, et al.. (2008). High-throughput stem-loop RT-PCR miRNA expression profiling using minute amounts of input RNA. Ghent University Academic Bibliography (Ghent University). 1 indexed citations
11.
Wang, Yulei, David N. Keys, Janice Au-Young, & Caifu Chen. (2008). MicroRNAs in embryonic stem cells. Journal of Cellular Physiology. 218(2). 251–255. 89 indexed citations
12.
Mestdagh, Pieter, Tom Feys, Nathalie Bernard‐Marissal, et al.. (2008). High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA. Nucleic Acids Research. 36(21). e143–e143. 242 indexed citations
13.
Wu, Hao, Jun‐Wei Xu, Zhiping P. Pang, et al.. (2007). Integrative genomic and functional analyses reveal neuronal subtype differentiation bias in human embryonic stem cell lines. Proceedings of the National Academy of Sciences. 104(34). 13821–13826. 116 indexed citations
14.
Gaur, Arti, David A. Jewell, Yu Liang, et al.. (2007). Characterization of MicroRNA Expression Levels and Their Biological Correlates in Human Cancer Cell Lines. Cancer Research. 67(6). 2456–2468. 586 indexed citations breakdown →
15.
He, Lin, Xingyue He, Lee P. Lim, et al.. (2007). A microRNA component of the p53 tumour suppressor network. Nature. 447(7148). 1130–1134. 2177 indexed citations breakdown →
16.
Chen, Caifu, et al.. (2007). Defining embryonic stem cell identity using differentiation-related microRNAs and their potential targets. Mammalian Genome. 18(5). 316–327. 91 indexed citations
17.
Schmittgen, Thomas D., Eun Joo Lee, Jinmai Jiang, et al.. (2007). Real-time PCR quantification of precursor and mature microRNA. Methods. 44(1). 31–38. 495 indexed citations
18.
Gaur, Arti, David A. Jewell, Dana Ridzon, et al.. (2006). Characterization of microRNA expression and their biological correlates in the NCI-60 panel of human tumor derived cell lines. Cancer Research. 66. 981–981. 1 indexed citations
19.
Strauss, William M., et al.. (2006). Nonrestrictive developmental regulation of microRNA gene expression. Mammalian Genome. 17(8). 833–840. 54 indexed citations
20.
Lao, Kaiqin, et al.. (2006). Multiplexing RT-PCR for the detection of multiple miRNA species in small samples. Biochemical and Biophysical Research Communications. 343(1). 85–89. 117 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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