Ming‐Tat Ling

3.0k citations
51 papers · 2.5k · h-index 29

Impact in

    • Cancer-related molecular mechanisms research
  • Oncology top 5%
    • Cancer Cells and Metastasis
    • Cancer-related Molecular Pathways

Papers in

    • TGF-β signaling in diseases 6
    • DNA Repair Mechanisms 5
    • Cancer-related Molecular Pathways 7
    • Cancer Cells and Metastasis 6

Ming‐Tat Ling

51 papers receiving 2.4k citations

Peers

Ming‐Tat Ling
Comparison fields: 5 of 109
  • Cancer Research 531
  • Oncology 798
  • Geriatrics and Gerontology 111
  • Molecular Biology 1.6k
  • Cell Biology 344
Replace Liang Cheng with:
Liang Cheng China
Meidan Ying China
Toshiyuki Sakamaki United States
Jen-Liang Su Taiwan
Amro Aboukameel United States
Yiyu Zou United States
Alexandre Puissant France
Christina G. Towers United States
Pascal Colosetti France
Tomohisa Yokoyama Japan
Ming‐Tat Ling relative to Liang Cheng China Liang Cheng's profile →
Citations per field
00.5×3.4×
Liang Cheng · 1×
Citations per year

Countries citing papers authored by Ming‐Tat Ling

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Tat Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Tat Ling. 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 Ming‐Tat Ling. The network helps show where Ming‐Tat Ling may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005392
2 2011157
3 2003131
4 200593
5 201490
6 200689
7 201484
8 200283
9 201071
10 200771
11 200571
12 200670
13 200568
14 201367
15 200767
16 200759
17 199952
18 200550
19 201747
20 200546

About Ming‐Tat Ling

Ming‐Tat Ling is a scholar working on Molecular Biology, Oncology, Cancer Research, Pulmonary and Respiratory Medicine and Cell Biology, having authored 51 papers that have together received 2.5k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (7 papers), Cancer-related Molecular Pathways (7 papers), Cancer, Lipids, and Metabolism (6 papers), Cancer Cells and Metastasis (6 papers), TGF-β signaling in diseases (6 papers), Cancer-related molecular mechanisms research (6 papers), Microtubule and mitosis dynamics (5 papers) and DNA Repair Mechanisms (5 papers). The work is most often cited by research in Cancer Research (531 citations), Oncology (798 citations), Geriatrics and Gerontology (111 citations), Molecular Biology (1.6k citations) and Cell Biology (344 citations). Ming‐Tat Ling has collaborated with scholars based in Hong Kong, Australia and United States. Frequent co-authors include Xianghong Wang, Yong‐Chuan Wong, Xiaomeng Zhang, Xianghong Wang, Chee Wai Chua, Chun Zhou, Yong-Chuan Wong, Terence K. Lee, Yong Chuan Wong and Franky Leung Chan. Their work appears in journals such as Cancer Research, International Journal of Cancer, PLoS ONE, Carcinogenesis and Journal of Molecular Biology.

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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