Bin Ai

867 citations
47 papers · 603 · h-index 16

Impact in

Papers in

    • Plant and Fungal Species Descriptions 5
    • Genomics and Phylogenetic Studies 5
    • Lung Cancer Research Studies 3

Bin Ai

47 papers receiving 577 citations

Peers

Bin Ai
Comparison fields: 5 of 114
  • Ecology, Evolution, Behavior and Systematics 129
  • Media Technology 44
  • Genetics 128
  • Neuropsychology and Physiological Psychology 6
  • Plant Science 112
Replace Xiangdong Liu with:
Xiangdong Liu China
Yoshinobu Hoshino Japan
Xiaojuan Zhang China
Yiyun Li China
John C. Schultz United States
Sandy Y. M. Ng Canada
Gerald Bergtrom United States
Véronique Letort France
Mingyang Li China
Sarah E. Allen United States
Bin Ai relative to Xiangdong Liu China Xiangdong Liu's profile →
Citations per field
00.5×7.3×
Xiangdong Liu · 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 201564
2 201446
3 200844
4 200839
5
Paclitaxel targets VEGF-mediated angiogenesis in ovarian cancer treatment.
201627
6 201726
7 202325
8 202123
9 202121
10 200920
11 202019
12 201619
13 201419
14
Genetic variation in island and mainland populations of Ficus pumila (Moraceae) in eastern Zhejiang of China
200818
15 202418
16 201216
17 201914
18 201413
19 201612
20 201511

About Bin Ai

Bin Ai is a scholar working on Molecular Biology, Oncology, Genetics, Plant Science and Pulmonary and Respiratory Medicine, having authored 47 papers that have together received 603 indexed citations. Recurring topics across this work include Plant and Fungal Species Descriptions (5 papers), Genetic diversity and population structure (5 papers), Genomics and Phylogenetic Studies (5 papers), Lung Cancer Treatments and Mutations (5 papers), Remote Sensing and Land Use (4 papers), Health disparities and outcomes (4 papers), Lung Cancer Research Studies (3 papers) and Remote-Sensing Image Classification (3 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (129 citations), Media Technology (44 citations), Genetics (128 citations), Neuropsychology and Physiological Psychology (6 citations) and Plant Science (112 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 Chemical Engineering Journal, Scientific Reports, Molecular Ecology Resources, Photogrammetric Engineering & Remote Sensing and Symbiosis.

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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