Yan Wang

6.7k total citations · 1 hit paper
263 papers, 4.8k citations indexed

About

Yan Wang is a scholar working on Molecular Biology, Materials Chemistry and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yan Wang has authored 263 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Molecular Biology, 48 papers in Materials Chemistry and 40 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yan Wang's work include Bioinformatics and Genomic Networks (27 papers), Cancer-related molecular mechanisms research (23 papers) and Machine Learning in Bioinformatics (22 papers). Yan Wang is often cited by papers focused on Bioinformatics and Genomic Networks (27 papers), Cancer-related molecular mechanisms research (23 papers) and Machine Learning in Bioinformatics (22 papers). Yan Wang collaborates with scholars based in China, United States and United Kingdom. Yan Wang's co-authors include Ying‐Wei Yang, Dihua Dai, Chunyu Wang, Jie Yang, Jia‐Rui Wu, Zheng Li, Lan Huang, Dongmei Zhang, Xiao‐Bing Cui and Hongwei Qin and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and Advanced Materials.

In The Last Decade

Yan Wang

235 papers receiving 4.7k citations

Hit Papers

Supramolecular Assembly-Induced Emission Enhancement for ... 2019 2026 2021 2023 2019 100 200 300
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. Supramolecular Assembly-Induced Emission Enhancement for Efficient Mercury(II) Detection and Removal
    2019 352 citations Yan Wang, Ying‐Wei Yang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yan Wang China 37 1.5k 1.4k 622 559 533 263 4.8k
Lian Li China 40 1.3k 0.8× 834 0.6× 328 0.5× 356 0.6× 174 0.3× 281 6.4k
Chi Zhang China 52 3.0k 1.9× 1.8k 1.3× 242 0.4× 203 0.4× 188 0.4× 193 8.4k
Xiaohui Liu China 27 672 0.4× 788 0.6× 342 0.5× 161 0.3× 300 0.6× 149 2.6k
Jinchao Zhang China 56 4.0k 2.6× 3.5k 2.4× 1.3k 2.0× 417 0.7× 427 0.8× 434 12.9k
Guilan Wang China 44 1.2k 0.8× 2.7k 1.9× 175 0.3× 1.0k 1.8× 349 0.7× 204 6.8k
Lei Xie United States 44 2.9k 1.9× 1.5k 1.1× 436 0.7× 77 0.1× 240 0.5× 185 6.2k
Dawei Qi China 29 999 0.6× 1.3k 0.9× 739 1.2× 840 1.5× 259 0.5× 144 4.7k
Tatsuo Arai Japan 44 768 0.5× 3.0k 2.1× 2.1k 3.4× 677 1.2× 117 0.2× 742 10.3k
Guozhen Zhang China 40 401 0.3× 3.1k 2.2× 464 0.7× 207 0.4× 446 0.8× 264 6.0k
Jiaojiao Zhao China 36 384 0.2× 1.3k 0.9× 323 0.5× 73 0.1× 268 0.5× 161 5.0k

Countries citing papers authored by Yan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Wang. A scholar is included among the top collaborators of Yan 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 Yan Wang. Yan 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.
Zhang, Kun, Xin‐Yue Lou, Yan Wang, Weiwei Huan, & Ying‐Wei Yang. (2024). Emission enhancement induced by the supramolecular assembly of leggero pillar[5]arenes for the detection and separation of silver ions. Chinese Chemical Letters. 36(6). 110464–110464. 6 indexed citations
2.
Jiang, Zekun, et al.. (2024). Partial Label Learning with a Partner. Proceedings of the AAAI Conference on Artificial Intelligence. 38(13). 15029–15037.
3.
Hassan, Muhammad, Yan Wang, Di Wang, et al.. (2024). Deep learning model for human-intuitive shoeprint reconstruction. Expert Systems with Applications. 249. 123704–123704. 1 indexed citations
4.
5.
Wang, Yan, et al.. (2024). Graph pooling in graph neural networks: methods and their applications in omics studies. Artificial Intelligence Review. 57(11). 6 indexed citations
6.
7.
Wang, Yan, et al.. (2024). Multi-Omics Profiling Unveils the Complexity and Dynamics of Immune Infiltrates in Intrahepatic Cholangiocarcinoma. Biology. 13(10). 816–816. 2 indexed citations
8.
Wang, Xinfei, Lan Huang, Yan Wang, et al.. (2024). A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers. Briefings in Bioinformatics. 25(6). 5 indexed citations
9.
Wang, Yan, et al.. (2024). Construction of a Dataset for All Expressed Transcripts for Alzheimer’s Disease Research. Brain Sciences. 14(12). 1180–1180. 1 indexed citations
10.
Lu, Yifan, Ziqi Zhang, Chunfeng Yuan, et al.. (2024). Set Prediction Guided by Semantic Concepts for Diverse Video Captioning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(4). 3909–3917. 1 indexed citations
11.
Wang, Yan, et al.. (2024). Trends and Hotspots in Global Radiomics Research: A Bibliometric Analysis. Technology in Cancer Research & Treatment. 23. 2233977657–2233977657. 5 indexed citations
12.
Wang, Yan, Liming Guo, Qiong Zhou, et al.. (2023). OCMR: A comprehensive framework for optical chemical molecular recognition. Computers in Biology and Medicine. 163. 107187–107187. 2 indexed citations
13.
Wang, Yan. (2023). A Deep Learning-based Approach for Vision-based Weeds Detection. International Journal of Advanced Computer Science and Applications. 14(12). 2 indexed citations
14.
Wang, Yan, et al.. (2023). Prediction of Proteins in Cerebrospinal Fluid and Application to Glioma Biomarker Identification. Molecules. 28(8). 3617–3617. 3 indexed citations
15.
Yang, Lili, et al.. (2022). MMGraph: a multiple motif predictor based on graph neural network and coexisting probability for ATAC-seq data. Bioinformatics. 38(19). 4636–4638. 4 indexed citations
16.
Zhang, Shuangquan, Anjun Ma, Jing Zhao, et al.. (2021). Assessing deep learning methods in cis -regulatory motif finding based on genomic sequencing data. Briefings in Bioinformatics. 23(1). 17 indexed citations
17.
Wang, Yao, et al.. (2021). SGPNet: A Three‐Dimensional Multitask Residual Framework for Segmentation and IDH Genotype Prediction of Gliomas. Computational Intelligence and Neuroscience. 2021(1). 9 indexed citations
18.
Yang, Jinyu, Anjun Ma, Adam D. Hoppe, et al.. (2019). Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework. Nucleic Acids Research. 47(15). 7809–7824. 47 indexed citations
19.
Yang, Chen, Yan Wang, & Hui Xu. (2017). Treatment and Prevention of Skeletal Fluorosis.. PubMed. 30(2). 147–149. 27 indexed citations
20.
Zhang, Qiuping, Qinglan Li, Yan Wang, et al.. (2014). Covalent modification of graphene oxide with polynorbornene by surface-initiated ring-opening metathesis polymerization. Polymer. 55(23). 6044–6050. 40 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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