Xiaoping Min

464 total citations
34 papers, 336 citations indexed

About

Xiaoping Min is a scholar working on Molecular Biology, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xiaoping Min has authored 34 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 5 papers in Biomedical Engineering and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xiaoping Min's work include Machine Learning in Bioinformatics (5 papers), Protein Structure and Dynamics (5 papers) and RNA and protein synthesis mechanisms (5 papers). Xiaoping Min is often cited by papers focused on Machine Learning in Bioinformatics (5 papers), Protein Structure and Dynamics (5 papers) and RNA and protein synthesis mechanisms (5 papers). Xiaoping Min collaborates with scholars based in China, Spain and United States. Xiaoping Min's co-authors include Xiangxiang Zeng, Shengxiang Ge, Xiangrong Liu, Ningshao Xia, Quan Yuan, Liuwei Song, Jun Zhang, Chunyan Li, Siyi Zhu and Alfonso Rodríguez‐Patón and has published in prestigious journals such as Analytical Chemistry, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Xiaoping Min

31 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaoping Min China	10	218	104	46	44	30	34	336
Zan Armstrong United States	6	118 0.5×	51 0.5×	18 0.4×	11 0.3×	12 0.4×	8	281
Kyriakos Efthymiadis Belgium	9	84 0.4×	55 0.5×	35 0.8×	24 0.5×	15 0.5×	20	268
Yanjuan Li China	14	462 2.1×	82 0.8×	37 0.8×	11 0.3×	6 0.2×	35	581
Tung Thanh Hoang Vietnam	11	167 0.8×	25 0.2×	28 0.6×	16 0.4×	14 0.5×	44	439
Hasan Zulfiqar China	15	677 3.1×	17 0.2×	98 2.1×	31 0.7×	16 0.5×	27	815
Rafael E. O. Rocha Brazil	7	149 0.7×	32 0.3×	36 0.8×	15 0.3×	10 0.3×	20	211
Yunlong Cao China	10	77 0.4×	77 0.7×	13 0.3×	88 2.0×	13 0.4×	25	293
Zhaoqiang Liu China	9	95 0.4×	20 0.2×	18 0.4×	88 2.0×	56 1.9×	20	315
Yasha Ektefaie United States	6	70 0.3×	23 0.2×	24 0.5×	54 1.2×	48 1.6×	8	279
Nicolae Sapoval United States	6	167 0.8×	48 0.5×	16 0.3×	76 1.7×	6 0.2×	12	266

Countries citing papers authored by Xiaoping Min

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoping Min

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoping Min

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoping Min. A scholar is included among the top collaborators of Xiaoping Min 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 Xiaoping Min. Xiaoping Min is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Huang, Jianhua Z., Youli Zhang, Ziyang Wang, et al.. (2025). MambaPhase: deep learning for liquid–liquid phase separation protein classification. Briefings in Bioinformatics. 26(3).

Zhang, Liang, et al.. (2025). Identification of Key Biomarkers Related to Lipid Metabolism in Acute Pancreatitis and Their Regulatory Mechanisms Based on Bioinformatics and Machine Learning. Biomedicines. 13(9). 2132–2132.

Xie, Jun, Youli Zhang, Ziyang Wang, et al.. (2025). PPI-Graphomer: enhanced protein-protein affinity prediction using pretrained and graph transformer models. BMC Bioinformatics. 26(1). 116–116. 1 indexed citations

Min, Xiaoping, et al.. (2024). PB-GPT: An innovative GPT-based model for protein backbone generation. Structure. 32(10). 1820–1833.e5.

Wang, Tianshu, et al.. (2024). Empirical validation of ProteinMPNN’s efficiency in enhancing protein fitness. Frontiers in Genetics. 14. 1347667–1347667. 3 indexed citations

Min, Xiaoping, Jun Xie, Yang Huang, et al.. (2024). Tpgen: a language model for stable protein design with a specific topology structure. BMC Bioinformatics. 25(1). 35–35. 2 indexed citations

Zou, Jiajun, et al.. (2024). SurfPro-NN: A 3D point cloud neural network for the scoring of protein–protein docking models based on surfaces features and protein language models. Computational Biology and Chemistry. 110. 108067–108067. 4 indexed citations

Liu, Nan, Yang Huang, Xiaoping Min, et al.. (2023). PointDE: Protein Docking Evaluation Using 3D Point Cloud Neural Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(5). 3128–3138. 5 indexed citations

Min, Xiaoping, et al.. (2020). Comprehensive Review and Comparison of Anticancer Peptides Identification Models. Current Protein and Peptide Science. 22(3). 201–210. 8 indexed citations

10.

Min, Xiaoping, et al.. (2020). Sequence-Based Deep Learning Frameworks on Enhancer-Promoter Interactions Prediction. Current Pharmaceutical Design. 27(15). 1847–1855. 5 indexed citations

11.

Min, Xiaoping, et al.. (2019). Fruit Market Trend Forecast Using Kmeans-based Deep Learning Models. 628–633. 3 indexed citations

12.

Zhang, Qianqian, et al.. (2019). Parallel MOEA Based on Consensus and Membrane Structure for Inferring Phylogenetic Reconstruction. IEEE Access. 8. 6177–6189. 4 indexed citations

13.

Min, Xiaoping, Jianzhong Zhang, Wendi Chen, et al.. (2018). An automated microfluidic chemiluminescence immunoassay platform for quantitative detection of biomarkers. Biomedical Microdevices. 20(4). 91–91. 19 indexed citations

14.

Zhu, Siyi, et al.. (2018). Prediction of Drug–Gene Interaction by Using Metapath2vec. Frontiers in Genetics. 9. 248–248. 26 indexed citations

15.

Zeng, Xiangxiang, et al.. (2017). Predict the Relationship between Gene and Large Yellow Croaker’s Economic Traits. Molecules. 22(11). 1978–1978. 5 indexed citations

16.

Wu, Di, Liuwei Song, Quan Yuan, et al.. (2016). A Smartphone-Based Genotyping Method for Hepatitis B Virus at Point-of-Care Settings. SLAS TECHNOLOGY. 22(2). 122–129. 13 indexed citations

17.

Qiu, Xianbo, Liuwei Song, Shuo Yang, et al.. (2016). A fast and low-cost genotyping method for hepatitis B virus based on pattern recognition in point-of-care settings. Scientific Reports. 6(1). 28274–28274. 12 indexed citations

18.

Min, Xiaoping, et al.. (2016). WITHDRAWN: Benchmarking swarm intelligence clustering algorithms with case study of medical data. Computerized Medical Imaging and Graphics. 5 indexed citations

19.

Min, Xiaoping, et al.. (2014). Chemiluminescence Behavior of Luminol-KIO<sub>4</sub>-Ag Nanoparticles System and Its Analytical Applications. Journal of Biomedical Science and Engineering. 7(6). 307–315. 5 indexed citations

20.

Liu, Xiangrong, et al.. (2014). A uniform solution to integer factorization using time-free spiking neural P system. Neural Computing and Applications. 26(5). 1241–1247. 7 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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