Yue Xuan

2.1k total citations
26 papers, 1.1k citations indexed

About

Yue Xuan is a scholar working on Spectroscopy, Molecular Biology and Mechanical Engineering. According to data from OpenAlex, Yue Xuan has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Spectroscopy, 10 papers in Molecular Biology and 3 papers in Mechanical Engineering. Recurrent topics in Yue Xuan's work include Advanced Proteomics Techniques and Applications (12 papers), Mass Spectrometry Techniques and Applications (9 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Yue Xuan is often cited by papers focused on Advanced Proteomics Techniques and Applications (12 papers), Mass Spectrometry Techniques and Applications (9 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). Yue Xuan collaborates with scholars based in Germany, United States and China. Yue Xuan's co-authors include Lukas Reiter, Roland Bruderer, David Gómez‐Varela, Tejas Gandhi, Oliver M. Bernhardt, Julia Regina Sondermann, Manuela Schmidt, Brendan MacLean, Richard S. Johnson and Wei Tong and has published in prestigious journals such as Angewandte Chemie International Edition, Nature Communications and Nature Protocols.

In The Last Decade

Yue Xuan

24 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yue Xuan Germany 14 526 501 148 112 89 26 1.1k
Hang Li China 22 625 1.2× 184 0.4× 27 0.2× 76 0.7× 43 0.5× 78 1.3k
Zhenlin Chen China 16 443 0.8× 174 0.3× 189 1.3× 121 1.1× 71 0.8× 67 1.1k
Ziyi He China 23 511 1.0× 155 0.3× 39 0.3× 65 0.6× 361 4.1× 51 1.5k
Chengde Li China 17 136 0.3× 153 0.3× 339 2.3× 228 2.0× 37 0.4× 118 1.1k
Jiangning Wang China 15 213 0.4× 39 0.1× 35 0.2× 173 1.5× 126 1.4× 64 815
Mei Chen China 14 555 1.1× 32 0.1× 55 0.4× 57 0.5× 137 1.5× 39 889
Yingbin Li China 15 147 0.3× 49 0.1× 41 0.3× 86 0.8× 195 2.2× 71 683
R. Lemaire France 11 577 1.1× 822 1.6× 30 0.2× 24 0.2× 4 0.0× 16 1.1k
V. Shankar India 28 510 1.0× 28 0.1× 159 1.1× 208 1.9× 73 0.8× 125 2.2k
Yoshihiro Suwa Japan 18 321 0.6× 25 0.0× 247 1.7× 378 3.4× 67 0.8× 53 1.2k

Countries citing papers authored by Yue Xuan

Since Specialization
Citations

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

Fields of papers citing papers by Yue Xuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yue Xuan

This figure shows the co-authorship network connecting the top 25 collaborators of Yue Xuan. A scholar is included among the top collaborators of Yue Xuan 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 Yue Xuan. Yue Xuan 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.
Ogata, Kosuke, Ulises H. Guzmán, Yue Xuan, et al.. (2024). Extending the Coverage of Lys-C/Trypsin-Based Bottom-up Proteomics by Cysteine S-Aminoethylation. Journal of the American Society for Mass Spectrometry. 35(2). 386–396. 1 indexed citations
2.
Goetze, Sandra, Audrey van Drogen, Kyle L. Fort, et al.. (2024). Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA. Clinical Proteomics. 21(1). 26–26. 5 indexed citations
3.
Xuan, Yue, et al.. (2024). Effects of sulforaphane on prostate cancer stem cells-like properties: In vitro and molecular docking studies. Archives of Biochemistry and Biophysics. 762. 110216–110216. 2 indexed citations
4.
5.
Xu, Jin, Yalou Huang, Mingming Liu, et al.. (2024). Predicting Distant Drug-Target Interactions via a Random Walk Guided Graph Neural Network. 1536–1541. 1 indexed citations
6.
Fu, Qin, Niveda Sundararaman, Eugen Damoc, et al.. (2024). A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data‐Independent Acquisition Mass Spectrometry (DIA‐MS) Discovery. Angewandte Chemie International Edition. 63(52). e202409446–e202409446. 3 indexed citations
7.
Martínez‐Val, Ana, Kyle L. Fort, Giulia Franciosa, et al.. (2023). Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids. Nature Communications. 14(1). 3599–3599. 29 indexed citations
8.
Zhou, Yang, et al.. (2021). Autonomous detection of crop rows based on adaptive multi-ROI in maize fields. International journal of agricultural and biological engineering. 14(4). 217–225. 1 indexed citations
9.
Zhou, Yang, et al.. (2021). Autonomous detection of crop rows based on adaptive multi-ROI in maize fields. International journal of agricultural and biological engineering. 14(3). 217–225. 27 indexed citations
10.
Huang, Ting, Roland Bruderer, Jan Muntel, et al.. (2019). Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition. Molecular & Cellular Proteomics. 19(2). 421–430. 49 indexed citations
11.
Bennike, Tue Bjerg, Melena D. Bellin, Yue Xuan, et al.. (2018). A Cost-Effective High-Throughput Plasma and Serum Proteomics Workflow Enables Mapping of the Molecular Impact of Total Pancreatectomy with Islet Autotransplantation. Journal of Proteome Research. 17(5). 1983–1992. 22 indexed citations
12.
Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2017). Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results. Molecular & Cellular Proteomics. 16(12). 2296–2309. 305 indexed citations
13.
Bruderer, Roland, Oliver M. Bernhardt, Tejas Gandhi, et al.. (2017). WITHDRAWN: Heralds of parallel MS: Data-independent acquisition surpassing sequential identification of data dependent acquisition in proteomics. Molecular & Cellular Proteomics. mcp.M116.065730–mcp.M116.065730. 4 indexed citations
14.
Egertson, Jarrett D., Brendan MacLean, Richard S. Johnson, Yue Xuan, & Michael J. MacCoss. (2015). Multiplexed peptide analysis using data-independent acquisition and Skyline. Nature Protocols. 10(6). 887–903. 157 indexed citations
15.
Schräder, Wolfgang, Yue Xuan, & Andras Gaspar. (2014). Studying Ultra-Complex Crude Oil Mixtures by Using High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Coupled to an Electrospray Ionisation-LTQ-Orbitrap Mass Spectrometer. European Journal of Mass Spectrometry. 20(1). 43–49. 20 indexed citations
16.
Tong, Wei, Yue Xuan, & Hong Yao. (2011). On the Interaction of Material Heterogeneity and Geometric Discontinuity in Serrated Plastic Flows. 2 indexed citations
17.
Xuan, Yue, Andrew J. Creese, Julie A. Horner, & Helen J. Cooper. (2009). High‐field asymmetric waveform ion mobility spectrometry (FAIMS) coupled with high‐resolution electron transfer dissociation mass spectrometry for the analysis of isobaric phosphopeptides. Rapid Communications in Mass Spectrometry. 23(13). 1963–1969. 72 indexed citations
18.
Xuan, Yue, et al.. (2007). CE of phytosiderophores and related metal species in plants. Electrophoresis. 28(19). 3507–3519. 18 indexed citations
19.
20.

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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