Ao Li

4.7k total citations
148 papers, 3.3k citations indexed

About

Ao Li is a scholar working on Molecular Biology, Cancer Research and Artificial Intelligence. According to data from OpenAlex, Ao Li has authored 148 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Molecular Biology, 38 papers in Cancer Research and 31 papers in Artificial Intelligence. Recurrent topics in Ao Li's work include Gene expression and cancer classification (33 papers), Machine Learning in Bioinformatics (27 papers) and Bioinformatics and Genomic Networks (24 papers). Ao Li is often cited by papers focused on Gene expression and cancer classification (33 papers), Machine Learning in Bioinformatics (27 papers) and Bioinformatics and Genomic Networks (24 papers). Ao Li collaborates with scholars based in China, United States and Sweden. Ao Li's co-authors include Minghui Wang, Dongdong Sun, Jianing Xi, Minghui Wang, Huanqing Feng, Yu Xue, Xuebiao Yao, Haichun Li, Yi Shen and Minghui Wang and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Ao Li

130 papers receiving 3.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ao Li China 32 2.0k 823 751 488 436 148 3.3k
Chun-Hou Zheng China 34 2.5k 1.3× 652 0.8× 1.1k 1.4× 344 0.7× 1.1k 2.5× 261 4.5k
Giancarlo Mauri Italy 33 2.5k 1.3× 382 0.5× 1.0k 1.4× 274 0.6× 495 1.1× 287 4.7k
Ran Su China 38 3.5k 1.8× 370 0.4× 731 1.0× 844 1.7× 826 1.9× 105 5.5k
Minghui Wang China 23 995 0.5× 468 0.6× 661 0.9× 411 0.8× 263 0.6× 100 2.0k
Nguyen Quoc Khanh Le Taiwan 43 2.0k 1.0× 291 0.4× 611 0.8× 656 1.3× 207 0.5× 151 3.9k
Leyi Wei China 48 6.8k 3.5× 756 0.9× 751 1.0× 668 1.4× 604 1.4× 199 8.6k
Saurav Mallik India 27 832 0.4× 289 0.4× 447 0.6× 257 0.5× 195 0.4× 188 2.1k
Alfredo Pulvirenti Italy 34 1.5k 0.7× 733 0.9× 362 0.5× 180 0.4× 288 0.7× 177 3.7k
Ivan G. Costa Germany 39 3.0k 1.5× 672 0.8× 634 0.8× 108 0.2× 189 0.4× 124 4.9k
Jun Sese Japan 27 1.9k 1.0× 226 0.3× 518 0.7× 241 0.5× 280 0.6× 82 3.6k

Countries citing papers authored by Ao Li

Since Specialization
Citations

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

Fields of papers citing papers by Ao Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ao Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ao Li. A scholar is included among the top collaborators of Ao Li based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ao Li. Ao Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Dengxiong, et al.. (2025). Advances in nanomaterials for enhancing cGAS-STING pathway mediated anti-tumor treatment. Materials Today Bio. 34. 102190–102190. 1 indexed citations
2.
Li, Ao, Lingyun Hu, Can Wang, et al.. (2025). Artificial Intelligence-Driven de Novo Design of Robust Enzymes to Enhance Their Performance. ACS Synthetic Biology. 14(11). 4178–4201.
3.
Huang, Mingxin, et al.. (2025). Artificial Intelligence-driven image analysis for standardised programmed death-ligand 1 expression evaluation in non-small cell lung cancer. Diagnostic Pathology. 20(1). 106–106. 1 indexed citations
4.
Zheng, Binbin, et al.. (2025). Enhancing collaboration between teacher and student for effective cross-domain nuclei detection and classification. Biomedical Signal Processing and Control. 106. 107763–107763.
5.
Li, Ao, et al.. (2024). Improved PM2.5 prediction with spatio-temporal feature extraction and chemical components: The RCG-attention model. The Science of The Total Environment. 955. 177183–177183.
6.
Liu, Honglei, et al.. (2024). Agnostic-Specific Modality Learning for Cancer Survival Prediction From Multiple Data. IEEE Journal of Biomedical and Health Informatics. 29(9). 6311–6322.
7.
Shi, Yi, et al.. (2024). MIF: Multi-Shot Interactive Fusion Model for Cancer Survival Prediction Using Pathological Image and Genomic Data. IEEE Journal of Biomedical and Health Informatics. 29(5). 3247–3258. 2 indexed citations
8.
Wang, Minghui, et al.. (2024). Seeking multi-view commonality and peculiarity: A novel decoupling method for lung cancer subtype classification. Expert Systems with Applications. 260. 125397–125397.
9.
Su, Lei, et al.. (2023). Dual consistency semi-supervised nuclei detection via global regularization and local adversarial learning. Neurocomputing. 529. 204–213. 3 indexed citations
10.
11.
Meng, Gang, et al.. (2023). Cross-Domain Nuclei Detection in Histopathology Images Using Graph-Based Nuclei Feature Alignment. IEEE Journal of Biomedical and Health Informatics. 28(1). 78–88. 3 indexed citations
12.
Su, Lei, et al.. (2023). Local augmentation based consistency learning for semi-supervised pathology image classification. Computer Methods and Programs in Biomedicine. 232. 107446–107446. 5 indexed citations
13.
Tian, Chenchen, et al.. (2022). Semi-Supervised Nuclei Detection in Histopathology Images via Location-Aware Adversarial Image Reconstruction. IEEE Access. 10. 42739–42749. 1 indexed citations
14.
Liu, Yu, et al.. (2021). TSDLPP: A Novel Two-Stage Deep Learning Framework For Prognosis Prediction Based on Whole Slide Histopathological Images. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19(4). 2523–2532. 6 indexed citations
15.
Wang, Minghui, et al.. (2017). A novel method for identifying potential disease-related miRNAs via a disease–miRNA–target heterogeneous network. Molecular BioSystems. 13(11). 2328–2337. 11 indexed citations
16.
Xi, Jianing, Minghui Wang, & Ao Li. (2017). Discovering potential driver genes through an integrated model of somatic mutation profiles and gene functional information. Molecular BioSystems. 13(10). 2135–2144. 20 indexed citations
17.
Sun, Dongdong, Ao Li, Huanqing Feng, & Minghui Wang. (2016). NTSMDA: prediction of miRNA–disease associations by integrating network topological similarity. Molecular BioSystems. 12(7). 2224–2232. 57 indexed citations
18.
Li, Ao, et al.. (2016). A Bipartite Network-Based Method for Prediction of Long Non-Coding RNA–Protein Interactions. Genomics Proteomics & Bioinformatics. 14(1). 62–71. 81 indexed citations
19.
Shen, Yi, et al.. (2015). Discovering key regulatory mechanisms from single-factor and multi-factor regulations in glioblastoma utilizing multi-dimensional data. Molecular BioSystems. 11(8). 2345–2353. 2 indexed citations
20.

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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