Gang Lan

598 citations
17 papers · 438 · h-index 11

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Cancer, Lipids, and Metabolism
  • Biochemistry top 10%
    • Sulfur Compounds in Biology

Papers in

    • MicroRNA in disease regulation 3
    • Cancer, Lipids, and Metabolism 3
    • Cancer-related molecular mechanisms research 2
    • Cholesterol and Lipid Metabolism 4

Gang Lan

16 papers receiving 432 citations

Peers

Gang Lan
Comparison fields: 5 of 77
  • Cancer Research 201
  • Biochemistry 47
  • Immunology 96
  • Molecular Biology 224
  • Surgery 114
Replace Handong Ma with:
Handong Ma China
Mian Yang China
Pin Qian China
Katrin Bennewitz Germany
Ju-Qiong Wang China
Yunwei Guo China
Jiro Ikeda Japan
Max Walker United States
Anke Loregger Netherlands
Tae‐Young Na South Korea
Gang Lan relative to Handong Ma China Handong Ma's profile →
Citations per field
00.5×3.1×
Handong Ma · 1×
Citations per year

Countries citing papers authored by Gang Lan

Since Specialization
Citations

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

Fields of papers citing papers by Gang Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 201666
2 201665
3 201644
4 201540
5 201540
6 201538
7 201636
8 201532
9 200824
10 202014
11 202011
12 202210
13 20239
14 20234
15 20234
16 20241
17 20240

About Gang Lan

Gang Lan is a scholar working on Cancer Research, Surgery, Molecular Biology, Immunology and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 438 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (4 papers), Cholesterol and Lipid Metabolism (4 papers), MicroRNA in disease regulation (3 papers), Cancer, Lipids, and Metabolism (3 papers), Inflammatory Biomarkers in Disease Prognosis (2 papers), Sulfur Compounds in Biology (2 papers), RNA Research and Splicing (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (201 citations), Biochemistry (47 citations), Immunology (96 citations), Molecular Biology (224 citations) and Surgery (114 citations). Gang Lan has collaborated with scholars based in China and Canada. Frequent co-authors include Chao‐Ke Tang, Xi‐Long Zheng, Wei Xie, Haipeng Cheng, Duo Gong, Feng Yao, Chong Huang, Zhen-Wang Zhao, Liang Li and Guiwu Wei. Their work appears in journals such as Biochemical and Biophysical Research Communications, International Journal of Molecular Sciences, Atherosclerosis, PLoS ONE and Medicine.

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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