Te Liu

3.0k citations
110 papers · 2.3k · h-index 27

Impact in

Papers in

    • RNA modifications and cancer 10
    • Pluripotent Stem Cells Research 9
    • Epigenetics and DNA Methylation 8
    • Circular RNAs in diseases 8
    • Extracellular vesicles in disease 8
    • MicroRNA in disease regulation 26
    • Cancer-related molecular mechanisms research 12

Te Liu

104 papers receiving 2.3k citations

Peers

Te Liu
Comparison fields: 5 of 125
  • Cancer Research 784
  • Reproductive Medicine 150
  • Molecular Biology 1.3k
  • Oncology 328
  • Immunology 238
Replace Joseph Kwong with:
Joseph Kwong Hong Kong
Jonathan Krell United Kingdom
Caiping Ren China
Leping Li China
Seung Myung Dong South Korea
Jing Tan China
Jermaine Coward Australia
Te Liu relative to Joseph Kwong Hong Kong Joseph Kwong's profile →
Citations per field
00.5×3.7×
Joseph Kwong · 1×
Citations per year

Countries citing papers authored by Te Liu

Since Specialization
Citations

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

Fields of papers citing papers by Te Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Te Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Te Liu Line = papers co-authored together Te Liu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 110 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012202
2 2011103
3 2010101
4 201094
5 201286
6 202157
7 202152
8 202447
9 202245
10 201244
11 201743
12 202141
13 201640
14 201438
15 201238
16 202337
17 201537
18 201935
19 201733
20 201132

About Te Liu

Te Liu is a scholar working on Molecular Biology, Cancer Research, Immunology, Surgery and Pulmonary and Respiratory Medicine, having authored 110 papers that have together received 2.3k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (26 papers), Cancer-related molecular mechanisms research (12 papers), RNA modifications and cancer (10 papers), Pluripotent Stem Cells Research (9 papers), Epigenetics and DNA Methylation (8 papers), Circular RNAs in diseases (8 papers), Extracellular vesicles in disease (8 papers) and Cancer Cells and Metastasis (7 papers). The work is most often cited by research in Cancer Research (784 citations), Reproductive Medicine (150 citations), Molecular Biology (1.3k citations), Oncology (328 citations) and Immunology (238 citations). Te Liu has collaborated with scholars based in China, United States and France. Frequent co-authors include Weiwei Cheng, Yongyi Huang, Yongtao Gao, Xiaoping Wan, Zixiang Geng, Lihe Guo, Hui Wang, Zhixue Liu, Dongmei Lai and Xiling Du. Their work appears in journals such as International Journal of Medical Sciences, International Journal of Molecular Medicine, Gene, International Journal of Biological Sciences and Drug Design Development and Therapy.

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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