Ting Ye

3.4k total citations · 1 hit paper
113 papers, 2.2k citations indexed

About

Ting Ye is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Ting Ye has authored 113 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 25 papers in Cancer Research and 22 papers in Oncology. Recurrent topics in Ting Ye's work include Cancer-related molecular mechanisms research (13 papers), MicroRNA in disease regulation (12 papers) and Cancer Cells and Metastasis (8 papers). Ting Ye is often cited by papers focused on Cancer-related molecular mechanisms research (13 papers), MicroRNA in disease regulation (12 papers) and Cancer Cells and Metastasis (8 papers). Ting Ye collaborates with scholars based in China, United States and Australia. Ting Ye's co-authors include Jingyuan Li, Qin Cheng, Jian Yang, Shao Jian Zheng, Chong Wei Jin, Wei Wei Chen, Dan Xie, Pei Qin, Xue Wan and Yihua Sun and has published in prestigious journals such as PLoS ONE, PLANT PHYSIOLOGY and Journal of Agricultural and Food Chemistry.

In The Last Decade

Ting Ye

105 papers receiving 2.1k citations

Hit Papers

Esophageal cancer in China: Practice and research in the ... 2022 2026 2023 2024 2022 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Esophageal cancer in China: Practice and research in the new era
    2022 115 citations Ting Ye et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting Ye China 25 958 493 404 346 320 113 2.2k
Sabrina Angelini Italy 28 1.2k 1.2× 641 1.3× 328 0.8× 318 0.9× 185 0.6× 94 2.7k
Zheng‐Guo Cui Japan 26 945 1.0× 304 0.6× 248 0.6× 192 0.6× 204 0.6× 103 2.3k
Anna Jakubowska Poland 33 1.7k 1.8× 886 1.8× 317 0.8× 388 1.1× 167 0.5× 188 3.8k
Zhenguo Zhao China 21 1.0k 1.1× 509 1.0× 118 0.3× 224 0.6× 140 0.4× 79 1.8k
Jingjing Hu China 29 1.3k 1.3× 770 1.6× 151 0.4× 289 0.8× 178 0.6× 105 2.3k
Sen Zhao China 27 1.0k 1.1× 417 0.8× 430 1.1× 126 0.4× 256 0.8× 131 2.2k
Francesca Rizzo Italy 30 1.5k 1.6× 620 1.3× 147 0.4× 194 0.6× 157 0.5× 106 2.7k
Chenchen Feng China 27 1.3k 1.3× 573 1.2× 354 0.9× 109 0.3× 350 1.1× 144 2.3k
Bo Zhu China 27 898 0.9× 179 0.4× 197 0.5× 207 0.6× 190 0.6× 100 2.2k

Countries citing papers authored by Ting Ye

Since Specialization
Citations

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

Fields of papers citing papers by Ting Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Ye. A scholar is included among the top collaborators of Ting Ye 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 Ting Ye. Ting Ye 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
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Zhan, Wei, et al.. (2024). Transcriptome analysis revealed changes in multiple genes in Larimichthys crocea under starvation stress. Aquaculture Reports. 35. 102025–102025. 3 indexed citations
4.
Zhu, Jiajie, et al.. (2024). QTL Mapping-Based Identification of Visceral White-Nodules Disease Resistance Genes in Larimichthys polyactis. International Journal of Molecular Sciences. 25(20). 10872–10872. 2 indexed citations
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Hussain, Quaid, Ting Ye, Sihui Li, et al.. (2023). Genome-Wide Identification and Expression Analysis of the Copper Transporter (COPT/Ctr) Gene Family in Kandelia obovata, a Typical Mangrove Plant. International Journal of Molecular Sciences. 24(21). 15579–15579. 8 indexed citations
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Pan, Qingjun, et al.. (2023). Efficacy and safety of sequential immunosuppressive treatment for severe IgA nephropathy: A retrospective study. Frontiers in Pharmacology. 14. 1093442–1093442. 3 indexed citations
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Zhang, Huihui, Shuai Li, Jinwen Chen, et al.. (2023). Correlation analysis between myocardial work indices and liver function classification in patients with hepatitis B cirrhosis: A study with non-invasive left ventricular pressure-strain loop. Frontiers in Cardiovascular Medicine. 10. 1126590–1126590. 3 indexed citations
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Yuan, Hui, et al.. (2023). Artificial neural network–based diagnostic models for lung cancer combining conventional indicators with tumor markers. Experimental Biology and Medicine. 248(10). 829–838. 5 indexed citations
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Shang, Chenjing, Ting Ye, Qiao Zhou, et al.. (2023). Genome-Wide Identification and Bioinformatics Analyses of Host Defense Peptides Snakin/GASA in Mangrove Plants. Genes. 14(4). 923–923. 10 indexed citations
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Li, Jingyuan, Xue Wan, Dan Xie, et al.. (2023). SPDEF enhances cancer stem cell-like properties and tumorigenesis through directly promoting GALNT7 transcription in luminal breast cancer. Cell Death and Disease. 14(8). 569–569. 6 indexed citations
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Gao, Xiaoping, Ting Ye, Yu L. Lei, et al.. (2023). Dendrobium officinale aqueous extract influences the immune response following vaccination against SARS-CoV-2. Biomedicine & Pharmacotherapy. 162. 114702–114702. 5 indexed citations
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Qin, Pei, et al.. (2022). Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis. Clinical Chemistry and Laboratory Medicine (CCLM). 60(12). 1974–1983. 76 indexed citations
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Ye, Ting, Jia Feng, Meng Cui, et al.. (2021). LncRNA MIAT Services as a Noninvasive Biomarker for Diagnosis and Correlated with Immune Infiltrates in Breast Cancer. International Journal of Women s Health. Volume 13. 991–1004. 27 indexed citations
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Ye, Ting, Jingyuan Li, Jia Feng, et al.. (2021). The subtype‐specific molecular function of SPDEF in breast cancer and insights into prognostic significance. Journal of Cellular and Molecular Medicine. 25(15). 7307–7320. 9 indexed citations
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Wang, Xuanyi, Youjin Hao, Bo Li, et al.. (2020). ExoBCD: a comprehensive database for exosomal biomarker discovery in breast cancer. Briefings in Bioinformatics. 22(3). 39 indexed citations
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Liu, Hongxing, Ting Ye, Karsoon Tan, et al.. (2019). Effects of stocking density on the growth performance, bacterial load and antioxidant response systems of noble scallop Chlamys nobilis. Fish & Shellfish Immunology. 92. 40–44. 14 indexed citations
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Cheng, Dewei, Hongxing Liu, Hongkuan Zhang, et al.. (2019). Differential expressions of HSP70 gene between golden and brown noble scallops Chlamys nobilis under heat stress and bacterial challenge. Fish & Shellfish Immunology. 94. 924–933. 30 indexed citations
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Wang, Rui, Yuan Li, Haichuan Hu, et al.. (2014). FGFR1/3 Tyrosine Kinase Fusions Define a Unique Molecular Subtype of Non–Small Cell Lung Cancer. Clinical Cancer Research. 20(15). 4107–4114. 116 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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