Ting Yan

2.4k citations
75 papers · 1.0k indexed · 1 hit paper · h-index 19

Impact in

Papers in

    • Cancer Immunotherapy and Biomarkers 8
    • Cancer Cells and Metastasis 8
    • MicroRNA in disease regulation 5

Ting Yan

68 papers receiving 1000 citations

Hit Papers

Current advances and challenges in CAR T-Cell therapy for solid tumors: tumor-associated antigens and the tumor microenvironment 2023 · 127 citations
12720232026202420254080120

Peers

Ting Yan
Comparison fields: 5 of 138
  • Oncology 308
  • Process Chemistry and Technology 27
  • Computer Networks and Communications 188
  • Cancer Research 106
  • Molecular Biology 340
Replace Haiying Zhou with:
Haiying Zhou China
Linfang Wang China
Jiayong Wang China
Syed Mohd Faisal India
Wenbo Wang China
Xiuqi Li China
Qingyong Chen China
Tianxiang Li China
Muhammad Nadeem Yousaf United States
Wei Mo China
Ting Yan relative to Haiying Zhou China Haiying Zhou's profile →
Citations per field
00.5×10×13.5×
Haiying Zhou · 1×
Citations per year

Countries citing papers authored by Ting Yan

Since Specialization
Citations

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

Fields of papers citing papers by Ting Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ting Yan, 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 Ting Yan Line = papers co-authored together Ting Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
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10 20232
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12 20237
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14 20238
15 202226
16 20221
17 20221
18 202028
19 202028
20 202018

About Ting Yan

Ting Yan is a scholar working on Oncology, Cancer Research, Molecular Biology, Dermatology and Sensory Systems, having authored 75 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (8 papers), Cancer Cells and Metastasis (8 papers), Pluripotent Stem Cells Research (7 papers), MicroRNA in disease regulation (5 papers), Ferroptosis and cancer prognosis (5 papers), Cancer-related gene regulation (5 papers), Extracellular vesicles in disease (5 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Oncology (308 citations), Process Chemistry and Technology (27 citations), Computer Networks and Communications (188 citations), Cancer Research (106 citations) and Molecular Biology (340 citations). Ting Yan has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Jin Chen, John A. Stankovic, Tarek Abdelzaher, Pascal Vicaire, Lin Gu, Tian He, Liqian Luo, Gang Zhou, Qing Cao and Radu Stoleru. Their work appears in journals such as Frontiers in Immunology, Frontiers in Pharmacology, Scientific Reports, Cancer Gene Therapy and Theranostics.

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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