Kuo‐Tai Hua

3.0k citations
62 papers · 2.3k indexed · h-index 30
    • MicroRNA in disease regulation 6
    • Cancer, Hypoxia, and Metabolism 5
    • Protease and Inhibitor Mechanisms 4
    • Cancer-related gene regulation 11
    • Epigenetics and DNA Methylation 10
    • RNA modifications and cancer 7
    • Histone Deacetylase Inhibitors Research 5
  • Oncology top 5%
    • Peptidase Inhibition and Analysis 4
  • Immunology top 10%

Kuo‐Tai Hua

60 papers receiving 2.3k citations

Peers

Kuo‐Tai Hua
Comparison fields: 5 of 102
  • Cancer Research 716
  • Molecular Biology 1.7k
  • Oncology 492
  • Immunology 293
  • Immunology and Allergy 44
Replace Ninel Azoitei with:
Ninel Azoitei Germany
Wenchao Liu China
Yung‐Luen Yu Taiwan
Liankang Sun China
Twee Tsao United States
Meidan Ying China
Kostyantyn Krysan United States
Linda Oyang China
Longzheng Xia China
Chunping Jiang China
Kuo‐Tai Hua relative to Ninel Azoitei Germany Ninel Azoitei's profile →
Citations per field
00.5×1.5×2.1×
Ninel Azoitei · 1×
Citations per year

Countries citing papers authored by Kuo‐Tai Hua

Since Specialization
Citations

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

Fields of papers citing papers by Kuo‐Tai Hua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuo‐Tai Hua. 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 Kuo‐Tai Hua. The network helps show where Kuo‐Tai Hua may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20245
2 202410
3 20245
4 20226
5 202021
6 202021
7 201916
8 201860
9 201748
10 2017128
11 201718
12 201614
13 201641
14 201541
15 201323
16 201340
17 201283
18 201139
19 2011125
20 2010297

About Kuo‐Tai Hua

Kuo‐Tai Hua is a scholar working on Cancer Research, Molecular Biology, Oncology, Applied Microbiology and Biotechnology and Immunology, having authored 62 papers that have together received 2.3k indexed citations. Recurring topics across this work include Cancer-related gene regulation (11 papers), Epigenetics and DNA Methylation (10 papers), RNA modifications and cancer (7 papers), MicroRNA in disease regulation (6 papers), Histone Deacetylase Inhibitors Research (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Peptidase Inhibition and Analysis (4 papers) and Protease and Inhibitor Mechanisms (4 papers). The work is most often cited by research in Cancer Research (716 citations), Molecular Biology (1.7k citations), Oncology (492 citations), Immunology (293 citations) and Immunology and Allergy (44 citations). Kuo‐Tai Hua has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Michael Hsiao, Min‐Liang Kuo, Ming‐Hsien Chien, Tsu‐Yao Cheng, Min-Wei Chen, Lin‐Hung Wei, Wei-Jiunn Lee, Jen-Liang Su, Ming‐Tsan Lin and Yi‐Hua Jan. Their work appears in journals such as Cancer Research, Cancer Letters, Oncogene, Annals of Surgical Oncology and Biochimica et Biophysica Acta (BBA) - Reviews on Cancer.

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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