Ming-Teh Chen

477 citations
15 papers · 379 · h-index 8

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Glioma Diagnosis and Treatment

Papers in

Ming-Teh Chen

15 papers receiving 373 citations

Peers

Ming-Teh Chen
Comparison fields: 5 of 60
  • Cancer Research 122
  • Genetics 60
  • Neurology 81
  • Cellular and Molecular Neuroscience 90
  • Molecular Biology 186
Replace Risa Kashima with:
Risa Kashima United States
Helena Storvall Sweden
Kristina Gotovac Croatia
Flavia Troglio Italy
Janani Sundaresan United States
Xueping Zheng China
Nektarios K. Mazarakis United Kingdom
Marina Cardano Italy
Peter Deng United States
Ming-Teh Chen relative to Risa Kashima United States Risa Kashima's profile →
Citations per field
00.5×1.5×2.4×
Risa Kashima · 1×
Citations per year

Countries citing papers authored by Ming-Teh Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Teh Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming-Teh Chen. 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-Teh Chen. The network helps show where Ming-Teh Chen may publish in the future.

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 201381
2 201679
3 200165
4 202055
5 200428
6 201526
7 201414
8 20078
9 20127
10 20076
11 20154
12 20123
13 20231
14 20151
15 20221

About Ming-Teh Chen

Ming-Teh Chen is a scholar working on Molecular Biology, Cancer Research, Genetics, Cellular and Molecular Neuroscience and Neurology, having authored 15 papers that have together received 379 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (3 papers), Meningioma and schwannoma management (3 papers), Glioma Diagnosis and Treatment (3 papers), Advanced biosensing and bioanalysis techniques (2 papers), Neurotransmitter Receptor Influence on Behavior (2 papers), Neurofibromatosis and Schwannoma Cases (2 papers), RNA modifications and cancer (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Cancer Research (122 citations), Genetics (60 citations), Neurology (81 citations), Cellular and Molecular Neuroscience (90 citations) and Molecular Biology (186 citations). Ming-Teh Chen has collaborated with scholars based in Taiwan, United States and Hong Kong. Frequent co-authors include Patricia H. Janak, Yi‐Ping Yang, Kai-Hsi Lu, Marisela Morales, Donald J. Woodward, Barry J. Hoffer, Pin‐I Huang, Yi‐Wei Chen, Hsin‐I Ma and Yueh Chien. Their work appears in journals such as Experimental Neurology, Cancers, World Neurosurgery, Behavioural Brain Research and Cancer Cell International.

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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