Bin Ai

47 papers receiving 548 citations

Peers

Bin Ai
Comparison fields: 5 of 119
  • Ecology, Evolution, Behavior and Systematics 145
  • Neuropsychology and Physiological Psychology 9
  • Media Technology 44
  • Genetics 132
  • Health 33
Replace Shaokui Ge with:
Shaokui Ge United States
Xiaojuan Zhang China
Xiangdong Liu China
Sandy Y. M. Ng Canada
Ye Sun China
Yoshinobu Hoshino Japan
John C. Schultz United States
Gerald Bergtrom United States
Xudong Yang China
Bin Ai relative to Shaokui Ge United States Shaokui Ge's profile →
Citations per field
00.5×10×13.2×
Shaokui Ge · 1×
Citations per year

Countries citing papers authored by Bin Ai

Since Specialization
Citations

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

Fields of papers citing papers by Bin Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201562
2 201446
3 200844
4 200839
5
Paclitaxel targets VEGF-mediated angiogenesis in ovarian cancer treatment.
201627
6 201726
7 202122
8 202322
9 202120
10 200920
11
Genetic variation in island and mainland populations of Ficus pumila (Moraceae) in eastern Zhejiang of China
200818
12 201418
13 202018
14 201618
15 201216
16 201914
17 201612
18 201511
19 201911
20 201411

About Bin Ai

Bin Ai is a scholar working on Molecular Biology, Oncology, Pulmonary and Respiratory Medicine, Genetics and Ecology, Evolution, Behavior and Systematics, having authored 47 papers that have together received 573 indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (8 papers), Plant and Fungal Species Descriptions (6 papers), Genomics and Phylogenetic Studies (5 papers), Genetic diversity and population structure (5 papers), Health disparities and outcomes (5 papers), Remote Sensing and Land Use (4 papers), Lung Cancer Research Studies (4 papers) and Plant Diversity and Evolution (4 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (145 citations), Neuropsychology and Physiological Psychology (9 citations), Media Technology (44 citations), Genetics (132 citations) and Health (33 citations). Bin Ai has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Ming Kang, Hongwen Huang, Yong Gao, Hanghui Kong, Xia Li, Junjie Tao, Xiaoyong Chen, Xiaoping Liu, Lin Liu and Jinqiang He. Their work appears in journals such as Scientific Reports, Chemical Engineering Journal, Frontiers in Immunology, International Journal of Environmental Research and Public Health and Archives of Gerontology and Geriatrics.

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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