Kai-Hsi Lu

529 citations
18 papers · 410 · h-index 10

Impact in

Papers in

    • Circular RNAs in diseases 3
    • RNA modifications and cancer 2
    • Epigenetics and DNA Methylation 1
    • MicroRNA in disease regulation 2
    • Cancer-related molecular mechanisms research 2

Kai-Hsi Lu

18 papers receiving 405 citations

Peers

Kai-Hsi Lu
Comparison fields: 5 of 60
  • Cancer Research 152
  • Reproductive Medicine 38
  • Genetics 41
  • Oncology 93
  • Molecular Biology 239
Replace Boxuan Liu with:
Boxuan Liu China
John So United States
Zaiju Huang China
Habibe Demir United States
Daniel Delgado‐Bellido Spain
Yuhuan Qiao China
Yong‐Jian Deng China
Janani Kumar Australia
Hélène Pendeville-Samain United States
Kirsty Ratcliffe United States
Kai-Hsi Lu relative to Boxuan Liu China Boxuan Liu's profile →
Citations per field
00.5×2×4×6×8.3×
Boxuan Liu · 1×
Citations per year

Countries citing papers authored by Kai-Hsi Lu

Since Specialization
Citations

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

Fields of papers citing papers by Kai-Hsi Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai-Hsi Lu. 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 Kai-Hsi Lu. The network helps show where Kai-Hsi Lu may publish in the future.

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 201682
2 201382
3 202055
4 201936
5 201734
6 201730
7 201924
8 201814
9 202213
10 200910
11 20239
12 20187
13 20215
14 20183
15 20252
16 20212
17 20201
18 20131

About Kai-Hsi Lu

Kai-Hsi Lu is a scholar working on Molecular Biology, Cancer Research, Reproductive Medicine, Pulmonary and Respiratory Medicine and Oncology, having authored 18 papers that have together received 410 indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (4 papers), Ferroptosis and cancer prognosis (3 papers), Circular RNAs in diseases (3 papers), MicroRNA in disease regulation (2 papers), Cancer Cells and Metastasis (2 papers), RNA modifications and cancer (2 papers), Cancer-related molecular mechanisms research (2 papers) and Epigenetics and DNA Methylation (1 paper). The work is most often cited by research in Cancer Research (152 citations), Reproductive Medicine (38 citations), Genetics (41 citations), Oncology (93 citations) and Molecular Biology (239 citations). Kai-Hsi Lu has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Yi‐Ping Yang, Ming-Teh Chen, Chi-Shuan Huang, Mong‐Lien Wang, Yueh Chien, Yi‐Wei Chen, Pin‐I Huang, Shou‐Dong Lee, Chian‐Shiu Chien and Ping‐Hsing Tsai. Their work appears in journals such as International Journal of Molecular Sciences, Biomedicines, Oncotarget, Phytomedicine 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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