Wenkai Wang

2.1k total citations · 2 hit papers
49 papers, 1.3k citations indexed

About

Wenkai Wang is a scholar working on Molecular Biology, Computer Networks and Communications and Materials Chemistry. According to data from OpenAlex, Wenkai Wang has authored 49 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 11 papers in Computer Networks and Communications and 9 papers in Materials Chemistry. Recurrent topics in Wenkai Wang's work include Machine Learning in Bioinformatics (7 papers), Protein Structure and Dynamics (6 papers) and Genomics and Phylogenetic Studies (4 papers). Wenkai Wang is often cited by papers focused on Machine Learning in Bioinformatics (7 papers), Protein Structure and Dynamics (6 papers) and Genomics and Phylogenetic Studies (4 papers). Wenkai Wang collaborates with scholars based in China, United States and Taiwan. Wenkai Wang's co-authors include Jianyi Yang, Zhenling Peng, Zhu Han, Husheng Li, Zongyang Du, Hong Wei, Hong Su, Yan Sun, Ivan Anishchenko and David Baker and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Wenkai Wang

40 papers receiving 1.3k citations

Hit Papers

The trRosetta server for fast and accurate protein struct... 2021 2026 2022 2024 2021 2023 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The trRosetta server for fast and accurate protein structure prediction
    2021 434 citations Zongyang Du, Hong Su et al. Nature Protocols profile →
  2. trRosettaRNA: automated prediction of RNA 3D structure with transformer network
    2023 100 citations Wenkai Wang, Chenjie Feng et al. Nature Communications profile →

Peers

Wenkai Wang
Lingfeng Chen China
Srinivas Chakravarthy United States
Qingxin Chen China
K. Venkatesan India
Anindya Basu India
Shaoliang Peng China
Xueling Li China
David Karig United States
Jian Yu China
Jinfeng Zhang China
Lingfeng Chen China
Wenkai Wang
Citations per year, relative to Wenkai Wang Wenkai Wang (= 1×) peers Lingfeng Chen

Countries citing papers authored by Wenkai Wang

Since Specialization
Citations

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

Fields of papers citing papers by Wenkai Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenkai Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Wenkai Wang. A scholar is included among the top collaborators of Wenkai 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 Wenkai Wang. Wenkai 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
1.
2.
Yang, De-Chang, Wenkai Wang, Minxi Zhang, & Guoliang Yu. (2025). Prediction of Hall anchor penetration depth using machine learning models. Ocean Engineering. 331. 121269–121269.
3.
Ni, Ying, Wenkai Wang, Yan Xu, & Wensheng Zhang. (2025). A study on the impact of polycyclic aromatic hydrocarbons (PAHs) on the risk of liver disease in middle-aged and older adults people based on the CHARLS database. Ecotoxicology and Environmental Safety. 300. 118493–118493.
4.
Wang, Wenkai, et al.. (2025). Impact of Echo Interference on Speech Intelligibility in Extra-Large Spaces. Buildings. 15(20). 3690–3690.
5.
Wang, Wenkai, Xianfeng Jia, Yinping Cao, et al.. (2024). A facile in-situ strategy to fabricate lightweight carbon fiber/silicone-phenolic aerogel composites with superior toughness and ablation performance. Journal of Materials Science. 59(39). 18488–18498. 2 indexed citations
6.
Wang, Wenkai, et al.. (2024). Low‐Frequency Trajectory Map‐Matching Method Based on Probability Interpolation. Transactions in GIS. 28(7). 2262–2280.
7.
8.
Jing, Ran, Wenkai Wang, & Hefei Hu. (2023). Dynamic Service Function Chain Deployment and Readjustment Method Based on Deep Reinforcement Learning. Sensors. 23(6). 3054–3054. 5 indexed citations
9.
Wang, Wenkai, Chenjie Feng, Renmin Han, et al.. (2023). trRosettaRNA: automated prediction of RNA 3D structure with transformer network. Nature Communications. 14(1). 7266–7266. 100 indexed citations breakdown →
10.
Wang, Wenkai, Zhenling Peng, & Jianyi Yang. (2022). Single-sequence protein structure prediction using supervised transformer protein language models. Nature Computational Science. 2(12). 804–814. 77 indexed citations
11.
Peng, Zhenling, Wenkai Wang, Renmin Han, Fa Zhang, & Jianyi Yang. (2022). Protein structure prediction in the deep learning era. Current Opinion in Structural Biology. 77. 102495–102495. 20 indexed citations
12.
Wang, Wenkai, Zhenling Peng, & Jianyi Yang. (2022). Source code and data for the paper "Single-sequence protein structure prediction using supervised transformer protein language models". Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
13.
Shang, Yan, et al.. (2021). Promoter engineering for high ectoine production in a lower saline medium by Halomonas hydrothermalis Y2. Biotechnology Letters. 43(4). 825–834. 10 indexed citations
14.
Du, Zongyang, Hong Su, Wenkai Wang, et al.. (2021). The trRosetta server for fast and accurate protein structure prediction. Nature Protocols. 16(12). 5634–5651. 434 indexed citations breakdown →
15.
Wang, Wenkai. (2020). Application of Blockchain in Targeted Poverty Alleviation. 6 indexed citations
16.
Wang, Wenkai, et al.. (2019). An Adaptive Iterative Algorithm for Motion Deblurring Based on Salient Intensity Prior. KSII Transactions on Internet and Information Systems. 13(2). 1 indexed citations
17.
Su, Qi, Tong Zheng Hong, Guohui Zhang, et al.. (2017). Toxicity and Efficacy of Chlorantraniliprole on Pieris rapae (Linnaeus) (Lepidoptera: Pieridae) on Cabbage. Journal of Agricultural Science. 9(2). 180–180. 8 indexed citations
18.
Sheng, Andong, et al.. (2012). Pseudo multi-hop distributed consensus algorithm under directed topologies. 67. 1616–1619.
19.
Lan, Dongming, et al.. (2011). A novel vector for expression cloning of large numbers of polymerase chain reaction products in Pichia pastoris. African Journal of Microbiology Research. 5(3). 211–216. 1 indexed citations
20.
Wang, Wenkai, et al.. (2010). Developing and Validating Service Innovation Readiness. Journal of the Association for Information Systems. 28(42). 71–59014. 2 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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