Shunfang Wang

847 total citations
79 papers, 533 citations indexed

About

Shunfang Wang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Atmospheric Science. According to data from OpenAlex, Shunfang Wang has authored 79 papers receiving a total of 533 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 22 papers in Computer Vision and Pattern Recognition and 10 papers in Atmospheric Science. Recurrent topics in Shunfang Wang's work include Machine Learning in Bioinformatics (34 papers), Genomics and Phylogenetic Studies (18 papers) and RNA and protein synthesis mechanisms (17 papers). Shunfang Wang is often cited by papers focused on Machine Learning in Bioinformatics (34 papers), Genomics and Phylogenetic Studies (18 papers) and RNA and protein synthesis mechanisms (17 papers). Shunfang Wang collaborates with scholars based in China and Hong Kong. Shunfang Wang's co-authors include Mingyuan Li, Shuhui Liu, Lei Guo, Yu Li, Shanshan Xu, Long Shu, Min Mu, Fangbiao Tao, Jie Sheng and Xueren Wang and has published in prestigious journals such as Bioinformatics, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Shunfang Wang

71 papers receiving 522 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shunfang Wang China 12 246 86 66 53 46 79 533
Julia Weng Taiwan 13 228 0.9× 4 0.0× 50 0.8× 12 0.2× 13 0.3× 21 513
Colleen Bushell United States 11 143 0.6× 29 0.3× 21 0.3× 8 0.2× 6 0.1× 20 364
Gen Li United States 14 161 0.7× 17 0.2× 56 0.8× 9 0.2× 1 0.0× 40 389
Smarti Reel United Kingdom 4 299 1.2× 27 0.3× 40 0.6× 4 0.1× 4 0.1× 5 537
Hoa N. Nguyen Vietnam 13 260 1.1× 50 0.6× 84 1.3× 40 0.8× 52 699
Ladislav Rampášek Canada 6 257 1.0× 22 0.3× 71 1.1× 20 0.4× 8 532
Melanie Osl Austria 9 173 0.7× 35 0.4× 129 2.0× 14 0.3× 18 404
Ying Sha China 10 102 0.4× 21 0.2× 182 2.8× 7 0.1× 2 0.0× 21 430
Peng Zeng United States 11 69 0.3× 30 0.3× 65 1.0× 4 0.1× 4 0.1× 41 475
Robab Sheikhpour Iran 8 80 0.3× 29 0.3× 122 1.8× 6 0.1× 5 0.1× 27 257

Countries citing papers authored by Shunfang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shunfang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shunfang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shunfang Wang. A scholar is included among the top collaborators of Shunfang Wang 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 Shunfang Wang. Shunfang Wang 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
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Wang, Xinyi & Shunfang Wang. (2024). ACP-PDAFF: Pretrained model and dual-channel attentional feature fusion for anticancer peptides prediction. Computational Biology and Chemistry. 112. 108141–108141. 3 indexed citations
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Wang, Shunfang, et al.. (2024). One-step multi-view clustering guided by weakened view-specific distribution. Expert Systems with Applications. 251. 124021–124021. 1 indexed citations
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Wang, Shunfang, et al.. (2024). Deeply integrating latent consistent representations in high-noise multi-omics data for cancer subtyping. Briefings in Bioinformatics. 25(2). 13 indexed citations
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Chen, Chao‐Wei, et al.. (2024). MSVM-UNet: Multi-Scale Vision Mamba UNet for Medical Image Segmentation. 3111–3114. 11 indexed citations
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Min, Wenwen, et al.. (2023). TsImpute: an accurate two-step imputation method for single-cell RNA-seq data. Bioinformatics. 39(12). 8 indexed citations
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Lv, Wenbing, et al.. (2023). MMS-Net: Multi-level multi-scale feature extraction network for medical image segmentation. Biomedical Signal Processing and Control. 86. 105330–105330. 24 indexed citations
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Wang, Shunfang, et al.. (2023). BFP-Net: Boundary Feature Pyramid for Medical Image Segmentation. 1362–1367.
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Li, X Rong, Wenwen Min, Jinyu Chen, Jiaxin Wu, & Shunfang Wang. (2023). TransVCOX: Bridging Transformer Encoder and Pre-trained VAE for Robust Cancer Multi-Omics Survival Analysis. 1254–1259. 1 indexed citations
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Wang, Shunfang, et al.. (2021). iEnhancer-RD: Identification of enhancers and their strength using RKPK features and deep neural networks. Analytical Biochemistry. 630. 114318–114318. 16 indexed citations
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Guo, Lei, et al.. (2019). Accurate classification of membrane protein types based on sequence and evolutionary information using deep learning. BMC Bioinformatics. 20(S25). 700–700. 27 indexed citations
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Liu, Gan, et al.. (2019). Prediction of oxidoreductase subfamily classes based on RFE-SND-CC-PSSM and machine learning methods. Journal of Bioinformatics and Computational Biology. 17(4). 1950029–1950029. 5 indexed citations
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Liu, Shuhui, et al.. (2015). Protein sub-nuclear location by fusing AAC and PSSM features based on sequence information. 236–239. 3 indexed citations
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Chen, Xiaolin, et al.. (2013). Improved median linear discriminant analysis for face recognition. 30. 1051–1055. 2 indexed citations
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Wang, Shunfang, et al.. (2007). Convergence Rate of Strong Consistency of the Maximum Likelihood Estimator in Exponential Family Nonlinear Models. Communication in Statistics- Theory and Methods. 36(1). 103–115. 1 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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