Ping Ji

6.8k total citations · 1 hit paper
95 papers, 5.1k citations indexed

About

Ping Ji is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Ping Ji has authored 95 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Molecular Biology, 22 papers in Oncology and 18 papers in Cancer Research. Recurrent topics in Ping Ji's work include RNA Research and Splicing (20 papers), RNA modifications and cancer (18 papers) and Cancer-related Molecular Pathways (8 papers). Ping Ji is often cited by papers focused on RNA Research and Splicing (20 papers), RNA modifications and cancer (18 papers) and Cancer-related Molecular Pathways (8 papers). Ping Ji collaborates with scholars based in United States, China and Germany. Ping Ji's co-authors include Carsten Müller‐Tidow, Wolfgang E. Berdel, Hubert Serve, Sven Diederichs, Ralf Metzger, Etmar Bulk, Paul M. Schneider, Michael Thomas, Wenbing Wang and Sebastian Böing and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Ping Ji

91 papers receiving 5.1k citations

Hit Papers

MALAT-1, a novel noncoding RNA, and thymosin β4 predict m... 2003 2026 2010 2018 2003 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping Ji United States 31 4.0k 2.6k 754 338 321 95 5.1k
Hui Ling China 36 3.4k 0.9× 2.6k 1.0× 717 1.0× 287 0.8× 316 1.0× 125 5.0k
Martin Zörnig Germany 32 4.6k 1.2× 2.8k 1.1× 768 1.0× 259 0.8× 909 2.8× 55 5.9k
Zhimin He China 36 3.0k 0.8× 1.4k 0.5× 1.2k 1.6× 284 0.8× 422 1.3× 108 4.2k
Irfan A. Asangani United States 28 4.5k 1.1× 3.1k 1.2× 765 1.0× 996 2.9× 378 1.2× 50 5.8k
Chunhong Yan United States 38 3.0k 0.8× 1.4k 0.5× 1.1k 1.5× 791 2.3× 428 1.3× 106 4.8k
Young Hee Ko United States 31 3.7k 0.9× 2.0k 0.8× 663 0.9× 360 1.1× 166 0.5× 69 5.1k
Atul Bedi United States 23 3.2k 0.8× 2.0k 0.8× 1.6k 2.2× 418 1.2× 639 2.0× 29 4.8k
Keizo Takenaga Japan 37 3.4k 0.9× 1.5k 0.6× 760 1.0× 257 0.8× 679 2.1× 139 4.8k
Jueheng Wu China 50 4.5k 1.1× 2.6k 1.0× 1.2k 1.5× 407 1.2× 619 1.9× 101 6.2k

Countries citing papers authored by Ping Ji

Since Specialization
Citations

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

Fields of papers citing papers by Ping Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ping Ji

This figure shows the co-authorship network connecting the top 25 collaborators of Ping Ji. A scholar is included among the top collaborators of Ping Ji 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 Ping Ji. Ping Ji 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.
Elrod, Nathan D., Hua Luo, Ping Ji, et al.. (2024). Regulation of the Drosophila transcriptome by Pumilio and the CCR4-NOT deadenylase complex. RNA. 30(7). rna.079813.123–rna.079813.123. 3 indexed citations
2.
Liu, Jingyi, Otis Pinkard, Helen C. Miranda, et al.. (2022). Suppression of premature transcription termination leads to reduced mRNA isoform diversity and neurodegeneration. Neuron. 110(8). 1340–1357.e7. 11 indexed citations
3.
Li, Lei, Kai-Lieh Huang, Ya Cui, et al.. (2021). An atlas of alternative polyadenylation quantitative trait loci contributing to complex trait and disease heritability. Nature Genetics. 53(7). 994–1005. 92 indexed citations
4.
Elrod, Nathan D., Chung-Te Chang, Lin Ai, et al.. (2021). Human Pumilio proteins directly bind the CCR4-NOT deadenylase complex to regulate the transcriptome. RNA. 27(4). 445–464. 40 indexed citations
5.
Chu, Yuan, Nathan D. Elrod, Chaojie Wang, et al.. (2019). Nudt21 regulates the alternative polyadenylation of Pak1 and is predictive in the prognosis of glioblastoma patients. Oncogene. 38(21). 4154–4168. 56 indexed citations
6.
Park, Hyun Jung, Ping Ji, Soyeon Kim, et al.. (2018). 3′ UTR shortening represses tumor-suppressor genes in trans by disrupting ceRNA crosstalk. Nature Genetics. 50(6). 783–789. 124 indexed citations
7.
Yuan, Fang, et al.. (2017). Inhibition of Notch1 protects against IL-1β-induced inflammation and cartilage destruction in temporomandibular chondrocytes. Molecular Medicine Reports. 15(6). 4391–4397. 16 indexed citations
8.
Yang, Jilong, Matti Annala, Ping Ji, et al.. (2014). Recurrent LRP1-SNRNP25 and KCNMB4-CCND3 fusion genes promote tumor cell motility in human osteosarcoma. Journal of Hematology & Oncology. 7(1). 76–76. 28 indexed citations
9.
Li, Xinyi, Yi Liu, Qing Wang, et al.. (2014). Two mature products of MIR-491 coordinate to suppress key cancer hallmarks in glioblastoma. Oncogene. 34(13). 1619–1628. 83 indexed citations
10.
Yang, Da, Yan Sun, Limei Hu, et al.. (2013). Integrated Analyses Identify a Master MicroRNA Regulatory Network for the Mesenchymal Subtype in Serous Ovarian Cancer. Cancer Cell. 23(2). 186–199. 314 indexed citations
11.
Holder, Alvin A., Patrick R. Taylor, Kyle A. Meyer, et al.. (2013). Preliminary anti-cancer photodynamic therapeutic in vitro studies with mixed-metal binuclear ruthenium(ii)–vanadium(iv) complexes. Dalton Transactions. 42(33). 11881–11881. 38 indexed citations
12.
Yang, Da, Yan Sun, Limei Hu, et al.. (2013). Integrated Analyses Identify a Master MicroRNA Regulatory Network for the Mesenchymal Subtype in Serous Ovarian Cancer. Cancer Cell. 23(5). 705–705. 6 indexed citations
13.
Song, Fangfang, Ping Ji, Hong Zheng, et al.. (2010). Definition of a Functional Single Nucleotide Polymorphism in the Cell Migration Inhibitory Gene MIIP That Affects the Risk of Breast Cancer. Cancer Research. 70(3). 1024–1032. 16 indexed citations
14.
Ji, Ping, Sarah M. Smith, Yingmei Wang, et al.. (2010). Inhibition of gliomagenesis and attenuation of mitotic transition by MIIP. Oncogene. 29(24). 3501–3508. 31 indexed citations
15.
16.
Liu, Chunquan, et al.. (2005). Effect of irradiation decontamination on the qualities of green tea. 19. 1 indexed citations
17.
Diederichs, Sven, Etmar Bulk, Björn Steffen, et al.. (2004). S100 Family Members and Trypsinogens Are Predictors of Distant Metastasis and Survival in Early-Stage Non-Small Cell Lung Cancer. Cancer Research. 64(16). 5564–5569. 168 indexed citations
18.
Wang, Wenbing, et al.. (2004). Deletion of Superoxide Dismutase Gene of Bombyx mori Nuclear Polyhedrosis Virus Affects Viral DNA Replication. International Journal of Industrial Entomology. 9(2). 225–228. 3 indexed citations
19.
Ji, Ping, Sven Diederichs, Wenbing Wang, et al.. (2003). MALAT-1, a novel noncoding RNA, and thymosin β4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene. 22(39). 8031–8041. 1844 indexed citations breakdown →
20.
Ji, Ping, et al.. (2000). The structural and functional analysis of egt gene of Bombyx mori nuclear polyhedrosis virus.. 16(1). 54–58. 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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