Kai Yu

3.2k total citations
42 papers, 1.2k citations indexed

About

Kai Yu is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Kai Yu has authored 42 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 8 papers in Genetics and 7 papers in Immunology. Recurrent topics in Kai Yu's work include RNA modifications and cancer (6 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers) and RNA Research and Splicing (5 papers). Kai Yu is often cited by papers focused on RNA modifications and cancer (6 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers) and RNA Research and Splicing (5 papers). Kai Yu collaborates with scholars based in United States, China and Taiwan. Kai Yu's co-authors include James A. Richardson, David M. Ornitz, Dražen Šošić, Eric N. Olson, Eleanor Feingold, Stephanie L. Sherman, Neil E. Lamb, John R. Shaffer, Vivian G. Cheung and Tiffany Oliver and has published in prestigious journals such as Cell, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Kai Yu

41 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kai Yu United States	16	671	238	228	183	182	42	1.2k
Gökçe Törüner United States	19	581 0.9×	376 1.6×	192 0.8×	213 1.2×	126 0.7×	86	1.4k
Vaidehi Jobanputra United States	23	456 0.7×	521 2.2×	207 0.9×	234 1.3×	86 0.5×	79	1.3k
Fabienne Brenet United States	13	890 1.3×	185 0.8×	211 0.9×	137 0.7×	197 1.1×	22	1.3k
Irina Golovleva Sweden	25	927 1.4×	284 1.2×	174 0.8×	225 1.2×	127 0.7×	78	1.9k
Fabian Beier Germany	20	1.1k 1.7×	228 1.0×	169 0.7×	243 1.3×	328 1.8×	84	2.0k
Masahiro Muto Japan	18	1.4k 2.1×	405 1.7×	123 0.5×	212 1.2×	188 1.0×	54	1.9k
Takafumi Matsumura Japan	25	752 1.1×	393 1.7×	154 0.7×	270 1.5×	175 1.0×	79	1.7k
Sergey I. Kutsev Russia	22	686 1.0×	457 1.9×	166 0.7×	104 0.6×	98 0.5×	216	1.6k
Dusica Babovic‐Vuksanovic United States	27	863 1.3×	540 2.3×	103 0.5×	118 0.6×	122 0.7×	99	2.2k
Jonathan M. Gerber United States	19	813 1.2×	125 0.5×	188 0.8×	384 2.1×	187 1.0×	57	1.7k

Countries citing papers authored by Kai Yu

Since Specialization

Citations

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

Fields of papers citing papers by Kai Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Yu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yu, Kai, Natalie Deuitch, Lea Cunningham, et al.. (2023). Genomic landscape of patients with germline RUNX1 variants and familial platelet disorder with myeloid malignancy. Blood Advances. 8(2). 497–511. 9 indexed citations

Bishop, Kevin, Kai Yu, Blake Carrington, et al.. (2022). Zrsr2 Is Essential for the Embryonic Development and Splicing of Minor Introns in RNA and Protein Processing Genes in Zebrafish. International Journal of Molecular Sciences. 23(18). 10668–10668. 5 indexed citations

Çelik, Alper, Xiaojun Yin, Kai Yu, et al.. (2022). Precision cut intestinal slices, a novel model of acute food allergic reactions. Allergy. 78(2). 500–511. 6 indexed citations

Bresciani, Erica, Blake Carrington, Kai Yu, et al.. (2021). Redundant mechanisms driven independently by RUNX1 and GATA2 for hematopoietic development. Blood Advances. 5(23). 4949–4962. 12 indexed citations

Yu, Kai, Huan Yang, Qiao‐Li Lv, et al.. (2021). Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma. Cancer Cell International. 21(1). 102–102. 8 indexed citations

Yu, Kai, Yuqiong Hu, Fan Wu, et al.. (2020). Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies. National Science Review. 7(8). 1306–1318. 98 indexed citations

Caruso, Francesca Pia, Luciano Garofano, Fulvio D’Angelo, et al.. (2020). A map of tumor–host interactions in glioma at single-cell resolution. GigaScience. 9(10). 31 indexed citations

Wang, Jing, Zhixian Wang, Yunpeng Zhu, et al.. (2020). Identify the Risk Factors of COVID-19-Related Acute Kidney Injury: A Single-Center, Retrospective Cohort Study. Frontiers in Medicine. 7. 436–436. 17 indexed citations

Wang, Li-Chong, Shuhui Chen, Xiaoli Shen, et al.. (2020). M6A RNA Methylation Regulator HNRNPC Contributes to Tumorigenesis and Predicts Prognosis in Glioblastoma Multiforme. Frontiers in Oncology. 10. 536875–536875. 67 indexed citations

10.

Saida, Satoshi, et al.. (2019). Gata2 deficiency delays leukemogenesis while contributing to aggressive leukemia phenotype in Cbfb-MYH11 knockin mice. Leukemia. 34(3). 759–770. 11 indexed citations

11.

Liu, Chang, Shiliang Liu, Zhixian Wang, et al.. (2018). Using the prostate imaging reporting and data system version 2 (PI-RIDS v2) to detect prostate cancer can prevent unnecessary biopsies and invasive treatment. Asian Journal of Andrology. 20(5). 459–459. 18 indexed citations

12.

Yu, Kai, et al.. (2016). Genetic alterations of HER genes in chromophobe renal cell carcinoma. Oncology Letters. 11(3). 2111–2116. 11 indexed citations

13.

Jin, Jianshi, Tengfei Lian, Chan Gu, et al.. (2016). The effects of cytosine methylation on general transcription factors. Scientific Reports. 6(1). 29119–29119. 41 indexed citations

14.

Gorczynski, Reginald M., et al.. (2010). CD200Fc(Gly)6TGFβ suppresses transplant rejection and MLCs in vitro (49.15). The Journal of Immunology. 184(Supplement_1). 49.15–49.15. 2 indexed citations

15.

Qiu, Chao, Kai Yu, Yue Li, et al.. (2008). Characterization of the major histocompatibility complex class II DQB (MhcMamu-DQB1) alleles in a cohort of Chinese rhesus macaques (Macaca mulatta). Human Immunology. 69(8). 513–521. 16 indexed citations

16.

Yu, Kai, Shuanglin Zhang, Ingrid B. Borecki, et al.. (2005). A Haplotype Similarity Based Transmission/Disequilibrium Test under Founder Heterogeneity. Annals of Human Genetics. 69(4). 455–467. 9 indexed citations

17.

Lamb, Neil E., Kai Yu, John R. Shaffer, Eleanor Feingold, & Stephanie L. Sherman. (2004). Association between Maternal Age and Meiotic Recombination for Trisomy 21. The American Journal of Human Genetics. 76(1). 91–99. 88 indexed citations

18.

Šošić, Dražen, James A. Richardson, Kai Yu, David M. Ornitz, & Eric N. Olson. (2003). Twist Regulates Cytokine Gene Expression through a Negative Feedback Loop that Represses NF-κB Activity. Cell. 112(2). 169–180. 375 indexed citations

19.

Yu, Kai & Eleanor Feingold. (2002). Methods for Analyzing the Spatial Distribution of Chiasmata During Meiosis Based on Recombination Data. Biometrics. 58(2). 369–377. 3 indexed citations

20.

Yu, Kai & Eleanor Feingold. (2001). Estimating the Frequency Distribution of Crossovers during Meiosis from Recombination Data. Biometrics. 57(2). 427–434. 11 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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