Liang He

54 papers receiving 814 citations

Peers

Liang He
Comparison fields: 5 of 110
  • Pathology and Forensic Medicine 100
  • Health, Toxicology and Mutagenesis 83
  • Rheumatology 79
  • Cell Biology 79
  • Molecular Biology 324
Replace Leigh G. Simpson with:
Leigh G. Simpson United States
Dagmar Führer‐Sakel Germany
Stephanie Morgan United States
Ruixia Zhu China
Dina C. Simes Portugal
Jin Geng China
Caterina Chiappetta Italy
Birgit Mentrup Germany
Changhong Chen China
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Liang He relative to Leigh G. Simpson United States Leigh G. Simpson's profile →
Citations per field
00.5×10×13.5×
Leigh G. Simpson · 1×
Citations per year

Countries citing papers authored by Liang He

Since Specialization
Citations

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

Fields of papers citing papers by Liang He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014131
2 201595
3 201865
4
Effect of NF-kB signaling pathway on the expression of MIF, TNF-α, IL-6 in the regulation of intervertebral disc degeneration.
201853
5 201540
6 201738
7 202236
8 201534
9 202034
10 202031
11 201827
12 202325
13 202520
14 201816
15 201715
16 201612
17 201511
18 20209
19 20258
20 20198

About Liang He

Liang He is a scholar working on Molecular Biology, Rheumatology, Surgery, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 61 papers that have together received 822 indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (6 papers), Osteoarthritis Treatment and Mechanisms (4 papers), Musculoskeletal pain and rehabilitation (3 papers), Air Quality and Health Impacts (2 papers), Receptor Mechanisms and Signaling (2 papers), Selenium in Biological Systems (2 papers), Estrogen and related hormone effects (2 papers) and Pancreatic function and diabetes (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (100 citations), Health, Toxicology and Mutagenesis (83 citations), Rheumatology (79 citations), Cell Biology (79 citations) and Molecular Biology (324 citations). Liang He has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jian Luo, Stefan Siwko, Mingjun Teng, Jiwei Tian, Zhixiang Zhou, Man Luo, Xinxing Liu, Xiaoping Chen, Chao Liu and Zhongyi Sun. Their work appears in journals such as Frontiers in Oncology, Medicine, Scientific Reports, Annals of Translational Medicine and Science Advances.

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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