Suyu Mei

774 total citations
35 papers, 581 citations indexed

About

Suyu Mei is a scholar working on Molecular Biology, Computational Theory and Mathematics and Pharmacology. According to data from OpenAlex, Suyu Mei has authored 35 papers receiving a total of 581 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 3 papers in Pharmacology. Recurrent topics in Suyu Mei's work include Machine Learning in Bioinformatics (21 papers), Bioinformatics and Genomic Networks (17 papers) and Computational Drug Discovery Methods (13 papers). Suyu Mei is often cited by papers focused on Machine Learning in Bioinformatics (21 papers), Bioinformatics and Genomic Networks (17 papers) and Computational Drug Discovery Methods (13 papers). Suyu Mei collaborates with scholars based in China, United States and Germany. Suyu Mei's co-authors include Kun Zhang, Hao Zhu, Fei Wang, Shuigeng Zhou, Erik K. Flemington, Kun Zhang, Kun Zhang, Georg Trummer and Ao Li and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and Scientific Reports.

In The Last Decade

Suyu Mei

34 papers receiving 575 citations

Peers

Suyu Mei
Tim Andersen United States
Artem Lysenko United Kingdom
Ramzan Umarov Saudi Arabia
Sunyoung Kwon South Korea
Shengli Zhang China
Vesna Memišević United States
Ehsaneddin Asgari United States
Cheng-Yan Kao Taiwan
Dan Ofer Israel
Daniel Berenberg United States
Tim Andersen United States
Suyu Mei
Citations per year, relative to Suyu Mei Suyu Mei (= 1×) peers Tim Andersen

Countries citing papers authored by Suyu Mei

Since Specialization
Citations

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

Fields of papers citing papers by Suyu Mei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suyu Mei

This figure shows the co-authorship network connecting the top 25 collaborators of Suyu Mei. A scholar is included among the top collaborators of Suyu Mei 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 Suyu Mei. Suyu Mei 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, Ao, et al.. (2025). Deep spectral clustering network for incomplete multi-view clustering. Engineering Applications of Artificial Intelligence. 148. 110387–110387. 1 indexed citations
2.
Mei, Suyu. (2025). Unravelling patterns of food tolerance to pesticide residues via non‐negative matrix factorization. Journal of Food Science. 90(2). e70029–e70029. 1 indexed citations
3.
4.
Mei, Suyu. (2024). Transferring knowledge across aquatic species via clustering techniques to unravel patterns of pesticide toxicity. The Science of The Total Environment. 950. 175385–175385. 1 indexed citations
5.
Mei, Suyu. (2024). Predicting health effects of food compounds via ensemble machine learning. International Journal of Food Science & Technology. 59(4). 2547–2557. 2 indexed citations
6.
Mei, Suyu. (2022). A machine learning framework for predicting synergistic and antagonistic drug combinatorial efficacy. Journal of Mathematical Chemistry. 60(4). 752–769. 4 indexed citations
7.
Mei, Suyu & Kun Zhang. (2021). A machine learning framework for predicting drug–drug interactions. Scientific Reports. 11(1). 17619–17619. 43 indexed citations
8.
Mei, Suyu & Kun Zhang. (2019). Neglog: Homology-Based Negative Data Sampling Method for Genome-Scale Reconstruction of Human Protein–Protein Interaction Networks. International Journal of Molecular Sciences. 20(20). 5075–5075. 8 indexed citations
9.
Mei, Suyu & Kun Zhang. (2019). A Multi-Label Learning Framework for Drug Repurposing. Pharmaceutics. 11(9). 466–466. 15 indexed citations
10.
Mei, Suyu & Kun Zhang. (2019). In silico unravelling pathogen-host signaling cross-talks via pathogen mimicry and human protein-protein interaction networks. Computational and Structural Biotechnology Journal. 18. 100–113. 12 indexed citations
11.
Mei, Suyu. (2018). In Silico Enhancing M. tuberculosis Protein Interaction Networks in STRING To Predict Drug-Resistance Pathways and Pharmacological Risks. Journal of Proteome Research. 17(5). 1749–1760. 6 indexed citations
12.
Mei, Suyu, Erik K. Flemington, & Kun Zhang. (2017). A computational framework for distinguishing directversusindirect interactions in human functional protein–protein interaction networks. Integrative Biology. 9(7). 595–606. 5 indexed citations
13.
Mei, Suyu & Kun Zhang. (2016). Computational discovery of Epstein-Barr virus targeted human genes and signalling pathways. Scientific Reports. 6(1). 30612–30612. 8 indexed citations
14.
15.
Mei, Suyu & Hao Zhu. (2015). A simple feature construction method for predicting upstream/downstream signal flow in human protein-protein interaction networks. Scientific Reports. 5(1). 17983–17983. 8 indexed citations
16.
17.
Mei, Suyu & Hao Zhu. (2014). Computational reconstruction of proteome-wide protein interaction networks between HTLV retroviruses and Homo sapiens. BMC Bioinformatics. 15(1). 245–245. 7 indexed citations
18.
Mei, Suyu & Hao Zhu. (2014). AdaBoost Based Multi-Instance Transfer Learning for Predicting Proteome-Wide Interactions between Salmonella and Human Proteins. PLoS ONE. 9(10). e110488–e110488. 26 indexed citations
19.
Mei, Suyu. (2011). Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization. Journal of Theoretical Biology. 293. 121–130. 81 indexed citations
20.
Mei, Suyu & Fei Wang. (2010). Amino acid classification based spectrum kernel fusion for protein subnuclear localization. BMC Bioinformatics. 11(S1). S17–S17. 33 indexed citations

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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