H. Lu

21 papers receiving 146 citations

Peers

H. Lu
Comparison fields: 5 of 62
  • Computational Mathematics 4
  • Cancer Research 38
  • Oncology 30
  • Psychiatry and Mental health 16
  • Molecular Biology 64
Replace Marijana Vanevski with:
Marijana Vanevski Australia
Clive Drakeford Ireland
Qibing Wu China
Bartosz Kapturkiewicz Poland
Zhuo Feng China
Ritam Chatterjee India
Zhibin Lin China
Qingxian Li China
Lingfeng Tong China
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Citations per field
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Citations per year

Countries citing papers authored by H. Lu

Since Specialization
Citations

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

Fields of papers citing papers by H. Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201323
2 201417
3 202113
4 202212
5
Efficacy of intra-tumor injection of Kang-Lai-Te in treating transplanted hepatoma in rats.
200412
6 202011
7 201711
8 201910
9 20206
10
[Association of the vitamin D receptor gene start codon polymorphism with vitamin D deficiency rickets].
20036
11 20085
12 20235
13 20214
14 20154
15 20232
16 20082
17 20231
18 20231
19 20251
20
[Detection of epidermal growth factor receptor gene mutations in non-small cell lung cancer using bi-loop probe specific primer quantitative PCR].
20111

About H. Lu

H. Lu is a scholar working on Molecular Biology, Oncology, Cancer Research, Cell Biology and Surgery, having authored 25 papers that have together received 149 indexed citations. Recurring topics across this work include RNA modifications and cancer (3 papers), Polynomial and algebraic computation (3 papers), Lung Cancer Treatments and Mutations (3 papers), Cytokine Signaling Pathways and Interactions (2 papers), Tensor decomposition and applications (2 papers), Epigenetics and DNA Methylation (2 papers), Cancer, Hypoxia, and Metabolism (2 papers) and Growth Hormone and Insulin-like Growth Factors (2 papers). The work is most often cited by research in Computational Mathematics (4 citations), Cancer Research (38 citations), Oncology (30 citations), Psychiatry and Mental health (16 citations) and Molecular Biology (64 citations). H. Lu has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Chaoqun Wang, Lili Gao, Liqun Wu, Lei Deng, Tongtong Pan, Feifei Na, Jianxin Xue, Cong Li, Bifei Huang and You Lü. Their work appears in journals such as Microbial Pathogenesis, Clinical Chemistry and Laboratory Medicine (CCLM), Molecular and Cellular Biochemistry, Cancer Management and Research and American Journal of Otolaryngology.

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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