Lin Liang

861 citations
37 papers · 594 · h-index 14

Impact in

    • Cancer-related molecular mechanisms research
    • Cancer, Lipids, and Metabolism
    • MicroRNA in disease regulation
    • Inflammatory Myopathies and Dermatomyositis

Papers in

Lin Liang

33 papers receiving 587 citations

Peers

Lin Liang
Comparison fields: 5 of 73
  • Cancer Research 121
  • Epidemiology 184
  • Physiology 25
  • Rheumatology 61
  • Immunology 78
Replace Živa Frangež with:
Živa Frangež Switzerland
Heekyong Bae United States
Bryan D. Bell United States
Kayla Martin United States
Luc‐Marie Gerland France
Monica Gonzales United States
Xueqian Yin United States
Arne Martens Belgium
Andrew Cross United Kingdom
Sharon Veenbergen Netherlands
Lin Liang relative to Živa Frangež Switzerland Živa Frangež's profile →
Citations per field
00.5×2.9×
Živa Frangež · 1×
Citations per year

Countries citing papers authored by Lin Liang

Since Specialization
Citations

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

Fields of papers citing papers by Lin Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020101
2 202273
3 202252
4 200843
5 202038
6 201934
7 202024
8 201823
9 201922
10 202219
11 202117
12 201717
13 202017
14 202214
15 201711
16 201910
17 202110
18 20249
19 20188
20 20188

About Lin Liang

Lin Liang is a scholar working on Epidemiology, Molecular Biology, Immunology, Physiology and Cancer Research, having authored 37 papers that have together received 594 indexed citations. Recurring topics across this work include Inflammatory Myopathies and Dermatomyositis (8 papers), Calcium signaling and nucleotide metabolism (4 papers), Adenosine and Purinergic Signaling (3 papers), RNA modifications and cancer (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), T-cell and B-cell Immunology (2 papers), Circular RNAs in diseases (2 papers) and Selenium in Biological Systems (2 papers). The work is most often cited by research in Cancer Research (121 citations), Epidemiology (184 citations), Physiology (25 citations), Rheumatology (61 citations) and Immunology (78 citations). Lin Liang has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Shaowei Wang, Linlin Ma, Dan Zhou, Yanhong Zhou, Qinglin Peng, Wentao Li, Qianjin Liao, Yanling Li, Yamei Zhang and Xin Lü. Their work appears in journals such as Frontiers in Cell and Developmental Biology, International Journal of Oncology, Clinical & Experimental Immunology, Biological Trace Element Research and Lara D. Veeken.

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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