Xiaozhe Wan

1.8k total citations · 1 hit paper
14 papers, 1.2k citations indexed

About

Xiaozhe Wan is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Xiaozhe Wan has authored 14 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Computational Theory and Mathematics and 3 papers in Materials Chemistry. Recurrent topics in Xiaozhe Wan's work include Computational Drug Discovery Methods (8 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (3 papers). Xiaozhe Wan is often cited by papers focused on Computational Drug Discovery Methods (8 papers), Protein Structure and Dynamics (4 papers) and Machine Learning in Materials Science (3 papers). Xiaozhe Wan collaborates with scholars based in China, Macao and United States. Xiaozhe Wan's co-authors include Mingyue Zheng, Hualiang Jiang, Xutong Li, Xiaohong Liu, Kaixian Chen, Dingyan Wang, Feisheng Zhong, Xiaomin Luo, Zhaojun Li and Zhaoping Xiong and has published in prestigious journals such as Bioinformatics, Journal of Medicinal Chemistry and Chemical Science.

In The Last Decade

Xiaozhe Wan

13 papers receiving 1.2k citations

Hit Papers

Pushing the Boundaries of Molecular Representation for Dr... 2019 2026 2021 2023 2019 200 400 600
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. Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism
    2019 645 citations Zhaoping Xiong, Dingyan Wang et al. Journal of Medicinal Chemistry profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaozhe Wan China 10 681 575 458 234 120 14 1.2k
Isidro Cortés‐Ciriano United Kingdom 26 874 1.3× 1.3k 2.3× 329 0.7× 430 1.8× 206 1.7× 63 2.3k
Michaël Moret Switzerland 12 418 0.6× 398 0.7× 290 0.6× 64 0.3× 144 1.2× 17 1.0k
Xutong Li China 20 1.2k 1.7× 1.1k 1.9× 715 1.6× 165 0.7× 26 0.2× 67 2.0k
Feisheng Zhong China 13 1.1k 1.7× 952 1.7× 671 1.5× 98 0.4× 35 0.3× 18 1.7k
Miquel Duran‐Frigola Spain 19 394 0.6× 696 1.2× 176 0.4× 110 0.5× 40 0.3× 46 1.2k
Agnieszka Szwajda Finland 14 817 1.2× 1.0k 1.8× 232 0.5× 105 0.4× 35 0.3× 16 1.4k
Jennifer J. Young United States 12 411 0.6× 1.5k 2.7× 145 0.3× 290 1.2× 118 1.0× 21 2.2k
Dingyan Wang China 22 1.2k 1.7× 1.2k 2.1× 761 1.7× 109 0.5× 18 0.1× 47 2.1k
Krishna C. Bulusu United Kingdom 12 451 0.7× 698 1.2× 92 0.2× 191 0.8× 108 0.9× 18 1.1k
Michael P. Menden Germany 15 489 0.7× 677 1.2× 68 0.1× 119 0.5× 87 0.7× 41 1.2k

Countries citing papers authored by Xiaozhe Wan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaozhe Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaozhe Wan

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

All Works

14 of 14 papers shown
1.
Xiong, Zhaoping, et al.. (2024). SciMind: A Multimodal Mixture-of-Experts Model for Advancing Pharmaceutical Sciences. 66–73. 1 indexed citations
2.
Wang, Jike, Hao Luo, Mingyang Wang, et al.. (2024). 3DSMILES-GPT: 3D molecular pocket-based generation with token-only large language model. Chemical Science. 16(2). 637–648. 16 indexed citations
3.
Wang, Xiaorui, Henry H. Y. Tong, Liwei Liu, et al.. (2024). Evaluation of AlphaFold2 Structures for Hit Identification across Multiple Scenarios. Journal of Chemical Information and Modeling. 64(9). 3630–3639. 4 indexed citations
4.
Wan, Xiaozhe, Xiaolong Wu, Dingyan Wang, et al.. (2022). An inductive graph neural network model for compound–protein interaction prediction based on a homogeneous graph. Briefings in Bioinformatics. 23(3). 17 indexed citations
5.
Zhong, Feisheng, Xiaolong Wu, Ruirui Yang, et al.. (2021). Drug target inference by mining transcriptional data using a novel graph convolutional network framework. Protein & Cell. 13(4). 281–301. 29 indexed citations
6.
Tan, Xiaoqin, Chunpu Li, Ruirui Yang, et al.. (2021). Discovery of Pyrazolo[3,4- d ]pyridazinone Derivatives as Selective DDR1 Inhibitors via Deep Learning Based Design, Synthesis, and Biological Evaluation. Journal of Medicinal Chemistry. 65(1). 103–119. 51 indexed citations
7.
Li, Xutong, Xiaolong Wu, Xiaozhe Wan, et al.. (2020). The application of artificial intelligence to drug sensitivity prediction. Chinese Science Bulletin (Chinese Version). 65(32). 3551–3561. 1 indexed citations
8.
Fu, Zunyun, Xutong Li, Zhaohui Wang, et al.. (2020). Optimizing chemical reaction conditions using deep learning: a case study for the Suzuki–Miyaura cross-coupling reaction. Organic Chemistry Frontiers. 7(16). 2269–2277. 35 indexed citations
9.
Li, Fei, Xiaozhe Wan, Jing Xing, et al.. (2019). Deep Neural Network Classifier for Virtual Screening Inhibitors of (S)-Adenosyl-L-Methionine (SAM)-Dependent Methyltransferase Family. Frontiers in Chemistry. 7. 324–324. 6 indexed citations
10.
Xiong, Zhaoping, Dingyan Wang, Xiaohong Liu, et al.. (2019). Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism. Journal of Medicinal Chemistry. 63(16). 8749–8760. 645 indexed citations breakdown →
11.
Li, Xutong, Zhaojun Li, Xiaolong Wu, et al.. (2019). Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation. Journal of Medicinal Chemistry. 63(16). 8723–8737. 62 indexed citations
12.
Li, Zhaojun, Xutong Li, Xiaohong Liu, et al.. (2019). KinomeX: a web application for predicting kinome-wide polypharmacology effect of small molecules. Bioinformatics. 35(24). 5354–5356. 36 indexed citations
13.
Xie, Chengying, Xiaozhe Wan, Haitian Quan, et al.. (2018). Preclinical characterization of anlotinib, a highly potent and selective vascular endothelial growth factor receptor‐2 inhibitor. Cancer Science. 109(4). 1207–1219. 263 indexed citations
14.
Jiang, Hao, Jing Xing, Chen Wang, et al.. (2017). Discovery of novel BET inhibitors by drug repurposing of nitroxoline and its analogues. Organic & Biomolecular Chemistry. 15(44). 9352–9361. 29 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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Breakdown of academic impact, for papers by Isidro Cortés‐Ciriano Breakdown of academic impact, for papers by Michaël Moret Breakdown of academic impact, for papers by Xutong Li Breakdown of academic impact, for papers by Feisheng Zhong Breakdown of academic impact, for papers by Miquel Duran‐Frigola Breakdown of academic impact, for papers by Agnieszka Szwajda Breakdown of academic impact, for papers by Jennifer J. Young Breakdown of academic impact, for papers by Dingyan Wang Breakdown of academic impact, for papers by Krishna C. Bulusu Breakdown of academic impact, for papers by Michael P. Menden
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