Ting Lan

1.7k citations
78 papers · 1.2k · h-index 19

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Extracellular vesicles in disease
    • RNA modifications and cancer
    • Circular RNAs in diseases
    • Epigenetics and DNA Methylation

Papers in

    • PI3K/AKT/mTOR signaling in cancer 9
    • Protein Kinase Regulation and GTPase Signaling 7
    • Epigenetics and DNA Methylation 6
    • DNA Repair Mechanisms 4
    • Receptor Mechanisms and Signaling 4
    • Ferroptosis and cancer prognosis 8

Ting Lan

75 papers receiving 1.2k citations

Peers

Ting Lan
Comparison fields: 5 of 96
  • Cancer Research 222
  • Molecular Biology 564
  • Pulmonary and Respiratory Medicine 198
  • Molecular Medicine 32
  • Neurology 50
Replace Shengjie Xu with:
Shengjie Xu China
Maryam Peymani Iran
Kai Zhao China
Hitomi Fujisaki Japan
Monica Lupi Italy
Norma Hernández‐Pedro Mexico
Haineng Xu China
Man Wu China
Chia‐Hung Hsieh Taiwan
Ting Lan relative to Shengjie Xu China Shengjie Xu's profile →
Citations per field
00.5×3.2×
Shengjie Xu · 1×
Citations per year

Countries citing papers authored by Ting Lan

Since Specialization
Citations

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

Fields of papers citing papers by Ting Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201472
2 202265
3 201959
4 202258
5 202252
6 201551
7 201643
8 202336
9 201335
10 201632
11 201931
12 202327
13 201827
14 202226
15 202126
16 201823
17 201522
18 201222
19 201919
20 201318

About Ting Lan

Ting Lan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Oncology, Cancer Research and Pathology and Forensic Medicine, having authored 78 papers that have together received 1.2k indexed citations. Recurring topics across this work include PI3K/AKT/mTOR signaling in cancer (9 papers), Ferroptosis and cancer prognosis (8 papers), Protein Kinase Regulation and GTPase Signaling (7 papers), Cancer-related molecular mechanisms research (7 papers), Epigenetics and DNA Methylation (6 papers), Cytokine Signaling Pathways and Interactions (5 papers), DNA Repair Mechanisms (4 papers) and Receptor Mechanisms and Signaling (4 papers). The work is most often cited by research in Cancer Research (222 citations), Molecular Biology (564 citations), Pulmonary and Respiratory Medicine (198 citations), Molecular Medicine (32 citations) and Neurology (50 citations). Ting Lan has collaborated with scholars based in China, United States and Ghana. Frequent co-authors include Yongchang Chen, Hai Qian, Min Wu, Jian Li, Ping Chen, Aibin Tao, Qian Li, Yan Wu, Bing Gu and Fei Yang. Their work appears in journals such as Cell Death and Disease, Cell Biology International, Molecular Neurobiology, PLoS ONE and RSC Advances.

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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