Bo Wen

19.8k total citations · 1 hit paper
132 papers, 3.9k citations indexed

About

Bo Wen is a scholar working on Molecular Biology, Spectroscopy and Epidemiology. According to data from OpenAlex, Bo Wen has authored 132 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Molecular Biology, 37 papers in Spectroscopy and 17 papers in Epidemiology. Recurrent topics in Bo Wen's work include Advanced Proteomics Techniques and Applications (30 papers), Metabolomics and Mass Spectrometry Studies (23 papers) and Mass Spectrometry Techniques and Applications (21 papers). Bo Wen is often cited by papers focused on Advanced Proteomics Techniques and Applications (30 papers), Metabolomics and Mass Spectrometry Studies (23 papers) and Mass Spectrometry Techniques and Applications (21 papers). Bo Wen collaborates with scholars based in China, United States and Denmark. Bo Wen's co-authors include Siqi Liu, Chunwei Zeng, Zhanlong Mei, Bing Zhang, Mingshe Zhu, William L. Fitch, Ruo Zhou, Kai Li, Sidney D. Nelson and Jun Wang and has published in prestigious journals such as Cell, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Bo Wen

128 papers receiving 3.8k citations

Hit Papers

metaX: a flexible and comprehensive software for processi... 2017 2026 2020 2023 2017 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bo Wen China 35 2.1k 677 504 387 363 132 3.9k
Qingsong Lin Singapore 44 2.6k 1.2× 406 0.6× 164 0.3× 494 1.3× 423 1.2× 154 5.2k
Dong Li China 28 2.0k 0.9× 217 0.3× 287 0.6× 249 0.6× 246 0.7× 124 3.3k
Éric Ezan France 38 2.7k 1.3× 770 1.1× 161 0.3× 630 1.6× 408 1.1× 107 5.1k
David Arndt Canada 12 4.3k 2.0× 307 0.5× 248 0.5× 853 2.2× 232 0.6× 19 7.2k
Jill Barber United Kingdom 32 1.4k 0.6× 439 0.6× 818 1.6× 218 0.6× 775 2.1× 146 4.1k
Yoichi Sakakibara Japan 27 1.7k 0.8× 150 0.2× 558 1.1× 235 0.6× 331 0.9× 150 3.8k
Wen‐Bin Yang Taiwan 40 2.4k 1.1× 187 0.3× 156 0.3× 536 1.4× 411 1.1× 161 4.8k
Daniela M. Tomazela Brazil 27 3.3k 1.6× 1.7k 2.5× 91 0.2× 472 1.2× 418 1.2× 53 5.8k
Rosalind E. Jenkins United Kingdom 41 2.1k 1.0× 429 0.6× 963 1.9× 87 0.2× 801 2.2× 103 5.1k
Lifang Liu China 30 1.6k 0.7× 119 0.2× 308 0.6× 459 1.2× 296 0.8× 183 3.0k

Countries citing papers authored by Bo Wen

Since Specialization
Citations

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

Fields of papers citing papers by Bo Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bo Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Bo Wen. A scholar is included among the top collaborators of Bo Wen 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 Bo Wen. Bo Wen 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.
Pérez‐Riverol, Yasset, Wout Bittremieux, William Stafford Noble, et al.. (2025). Open-Source and FAIR Research Software for Proteomics. Journal of Proteome Research. 24(5). 2222–2234. 6 indexed citations
2.
Wen, Bo, et al.. (2025). Quasi-dynamic modelling and performance analysis of double-row angular contact ball bearing considering overturning moment. European Journal of Mechanics - A/Solids. 116. 105924–105924.
3.
Wen, Bo, Chenwei Wang, Kai Li, et al.. (2025). DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterations. Nature Methods. 22(9). 1857–1867. 2 indexed citations
4.
Chen, Zhixiang, Harshil Dhruv, Xuqing Zhang, et al.. (2025). Development of PVTX-405 as a potent and highly selective molecular glue degrader of IKZF2 for cancer immunotherapy. Nature Communications. 16(1). 4095–4095. 6 indexed citations
5.
Liu, Lang, et al.. (2025). An Efficient High-Resolution Remote Sensing Object Detection Approach Using a Multilevel Optimized RT-DETR Model. IEEE Sensors Journal. 25(22). 42306–42315. 1 indexed citations
6.
Wen, Bo, et al.. (2025). Intelligent Virtual Dental Implant Placement via 3D Segmentation Strategy. Journal of Dental Research. 104(11). 1208–1217. 1 indexed citations
8.
Ahmed, Murtadha, et al.. (2024). BERT-ASC: Auxiliary-sentence construction for implicit aspect learning in sentiment analysis. Expert Systems with Applications. 258. 125195–125195. 4 indexed citations
9.
Bittremieux, Wout, et al.. (2024). Deep Learning Methods for De Novo Peptide Sequencing. Mass Spectrometry Reviews. 7 indexed citations
10.
Wen, Bo & William Stafford Noble. (2024). A multi-species benchmark for training and validating mass spectrometry proteomics machine learning models. Scientific Data. 11(1). 1207–1207. 1 indexed citations
11.
Su, Jianlin, et al.. (2024). Naive Bayes-based Context Extension for Large Language Models. 7791–7807. 2 indexed citations
12.
Kuznetsova, Ksenia G., Bo Wen, Stefan Johansson, et al.. (2022). Finding haplotypic signatures in proteins. GigaScience. 12. 4 indexed citations
13.
Zhang, Xinhui, Yanbin He, Zhiqiang Ruan, et al.. (2019). High-throughput identification of heavy metal binding proteins from the byssus of chinese green mussel (Perna viridis) by combination of transcriptome and proteome sequencing. PLoS ONE. 14(5). e0216605–e0216605. 12 indexed citations
14.
Hu, Qingsong, Chunlai Li, Shouyu Wang, et al.. (2019). LncRNAs-directed PTEN enzymatic switch governs epithelial–mesenchymal transition. Cell Research. 29(4). 286–304. 39 indexed citations
15.
Li, Ruijun, Fengyu Li, Qiang Feng, et al.. (2016). An LC-MS based untargeted metabolomics study identified novel biomarkers for coronary heart disease. Molecular BioSystems. 12(11). 3425–3434. 15 indexed citations
16.
Xie, Bing, Xiaofeng Li, Zhilong Lin, et al.. (2016). Prediction of Toxin Genes from Chinese Yellow Catfish Based on Transcriptomic and Proteomic Sequencing. International Journal of Molecular Sciences. 17(4). 556–556. 13 indexed citations
17.
Su, Longxiang, Ruo Zhou, Changting Liu, et al.. (2013). Urinary proteomics analysis for sepsis biomarkers with iTRAQ labeling and two-dimensional liquid chromatography–tandem mass spectrometry. The Journal of Trauma: Injury, Infection, and Critical Care. 74(3). 940–945. 25 indexed citations
18.
Yin, Xiao, Wen Wang, Wenjie Tan, et al.. (2011). [Enhancement of the immune response in mice with a noval HCV DNA vaccine targeting NS3 to dendritic cells].. PubMed. 27(1). 44–9. 1 indexed citations
19.
Jin, Mei, et al.. (2006). Study on sequence variation of mitochondrial cytochrome b gene and phlogenetic relationships of two kinds of Cashmere goats. 39(9). 1897–1901. 1 indexed citations
20.
Li, Yong-Nian, Li Zuo, Bo Wen, Wei Huang, & Jin Li. (2003). The Polymorphism Distribution of Y - chromosome Haplotypes in A Miao Population of Guizhou. 28(2). 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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