Lanqing Li

1.5k citations
54 papers · 998 · 1 hit paper · h-index 19

Impact in

Papers in

Lanqing Li

48 papers receiving 991 citations

Lanqing Li's Hit Papers

Hierarchical graph learning for protein–protein interaction 2023 · 120 citations
1200+1+2Years since publication4080120

Peers

Lanqing Li
Comparison fields: 5 of 129
  • Polymers and Plastics 260
  • Industrial and Manufacturing Engineering 84
  • Pollution 101
  • Electrical and Electronic Engineering 340
  • Water Science and Technology 81
Replace Chia‐Wei Lee with:
Chia‐Wei Lee Taiwan
Jianxin Huang China
Tianzhi Wang China
Yingzhe Li China
Babankumar S. Bansod India
Weimin Guo China
D. W. Bacon Canada
Yanlin Chen China
Xue Song Zhou China
Lanqing Li relative to Chia‐Wei Lee Taiwan Chia‐Wei Lee's profile →
Citations per field
00.5×1.5×2.4×
Chia‐Wei Lee · 1×
Citations per year

Countries citing papers authored by Lanqing Li

Since Specialization
Citations

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

Fields of papers citing papers by Lanqing Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022142
2
Hierarchical graph learning for protein–protein interaction
Hit paper breakdown →
2023120
3 202269
4 202163
5 202254
6 202246
7 202237
8 202334
9 200132
10 202227
11 202126
12 202225
13 202125
14 202321
15 202321
16 202421
17 202119
18 201419
19 202418
20 201918

About Lanqing Li

Lanqing Li is a scholar working on Electrical and Electronic Engineering, Polymers and Plastics, Molecular Biology, Artificial Intelligence and Health, Toxicology and Mutagenesis, having authored 54 papers that have together received 998 indexed citations. Recurring topics across this work include Organic Electronics and Photovoltaics (11 papers), Conducting polymers and applications (11 papers), Perovskite Materials and Applications (10 papers), Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (4 papers), Atmospheric chemistry and aerosols (3 papers), Air Quality and Health Impacts (3 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Polymers and Plastics (260 citations), Industrial and Manufacturing Engineering (84 citations), Pollution (101 citations), Electrical and Electronic Engineering (340 citations) and Water Science and Technology (81 citations). Lanqing Li has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Xiuheng Wang, Dou Luo, Aung Ko Ko Kyaw, Nanqi Ren, Peilin Zhao, Baomin Xu, Chengwei Shan, Zhengyan Jiang, Kai Wang and Jia Li. Their work appears in journals such as Advanced Energy Materials, Nature Communications, Nano Energy, Water Research and Environmental Pollution.

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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