Xiao‐Kang Lun

876 total citations
11 papers, 437 citations indexed

About

Xiao‐Kang Lun is a scholar working on Molecular Biology, Biophysics and Oncology. According to data from OpenAlex, Xiao‐Kang Lun has authored 11 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Biophysics and 2 papers in Oncology. Recurrent topics in Xiao‐Kang Lun's work include Single-cell and spatial transcriptomics (7 papers), Cell Image Analysis Techniques (6 papers) and Gene Regulatory Network Analysis (3 papers). Xiao‐Kang Lun is often cited by papers focused on Single-cell and spatial transcriptomics (7 papers), Cell Image Analysis Techniques (6 papers) and Gene Regulatory Network Analysis (3 papers). Xiao‐Kang Lun collaborates with scholars based in Switzerland, United States and Germany. Xiao‐Kang Lun's co-authors include Bernd Bodenmiller, Vito Riccardo Tomaso Zanotelli, Denis Schapiro, Hartland W. Jackson, Jana Fischer, Daniel Schulz, Stefanie Engler, Wilko Weichert, Ana Martín-Villalba and Daniel Brüne and has published in prestigious journals such as Nature Communications, Nature Biotechnology and Molecular Cell.

In The Last Decade

Xiao‐Kang Lun

10 papers receiving 432 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiao‐Kang Lun Switzerland	9	324	105	101	61	56	11	437
Erica S. Savig United States	5	408 1.3×	129 1.2×	89 0.9×	70 1.1×	147 2.6×	5	545
Alev Baysoy United States	4	391 1.2×	53 0.5×	141 1.4×	101 1.7×	108 1.9×	4	573
Christopher J. Sevinsky United States	10	253 0.8×	36 0.3×	116 1.1×	110 1.8×	30 0.5×	13	405
Benedict Anchang United States	7	253 0.8×	51 0.5×	122 1.2×	95 1.6×	55 1.0×	18	378
Mingyu Yang China	5	519 1.6×	86 0.8×	63 0.6×	121 2.0×	119 2.1×	9	626
Asif Rizwan United States	10	154 0.5×	59 0.6×	79 0.8×	122 2.0×	25 0.4×	16	414
Junyun Cheng China	8	423 1.3×	99 0.9×	42 0.4×	91 1.5×	95 1.7×	14	506
Samir Jain India	4	376 1.2×	117 1.1×	259 2.6×	142 2.3×	204 3.6×	9	666
Matthew R. Clutter United States	10	462 1.4×	126 1.2×	152 1.5×	44 0.7×	243 4.3×	17	720
Weiruo Zhang United States	7	175 0.5×	36 0.3×	83 0.8×	101 1.7×	66 1.2×	13	477

Countries citing papers authored by Xiao‐Kang Lun

Since Specialization

Citations

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

Fields of papers citing papers by Xiao‐Kang Lun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao‐Kang Lun. 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 Xiao‐Kang Lun. The network helps show where Xiao‐Kang Lun may publish in the future.

Co-authorship network of co-authors of Xiao‐Kang Lun

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

Giridharan, Thejaswini, Anzer Khan, Tiffany R. Emmons, et al.. (2025). Complement signaling as a T-cell checkpoint in the tumor microenvironment. Immunobiology. 230(4). 152951–152951.

Lun, Xiao‐Kang, Kuanwei Sheng, Yunhao Zhai, et al.. (2024). Signal amplification by cyclic extension enables high-sensitivity single-cell mass cytometry. Nature Biotechnology. 43(5). 811–821. 12 indexed citations

Kumar, Sunil, et al.. (2020). Stabilized Reconstruction of Signaling Networks from Single-Cell Cue-Response Data. Scientific Reports. 10(1). 1233–1233. 1 indexed citations

Lun, Xiao‐Kang & Bernd Bodenmiller. (2020). Profiling Cell Signaling Networks at Single-cell Resolution. Molecular & Cellular Proteomics. 19(5). 744–756. 29 indexed citations

Lun, Xiao‐Kang, et al.. (2020). A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids. Molecular Systems Biology. 16(12). e9798–e9798. 18 indexed citations

Lun, Xiao‐Kang, et al.. (2020). Mechanistic Model of Signaling Dynamics Across an Epithelial Mesenchymal Transition. Frontiers in Physiology. 11. 579117–579117. 9 indexed citations

Lun, Xiao‐Kang, Damian Szklarczyk, Attila Gábor, et al.. (2019). Analysis of the Human Kinome and Phosphatome by Mass Cytometry Reveals Overexpression-Induced Effects on Cancer-Related Signaling. Molecular Cell. 74(5). 1086–1102.e5. 32 indexed citations

Rapsomaniki, Maria Anna, Xiao‐Kang Lun, Stefan Woerner, et al.. (2018). CellCycleTRACER accounts for cell cycle and volume in mass cytometry data. Nature Communications. 9(1). 632–632. 28 indexed citations

Schulz, Daniel, Vito Riccardo Tomaso Zanotelli, Jana Fischer, et al.. (2017). Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry. Cell Systems. 6(1). 25–36.e5. 205 indexed citations

10.

Lun, Xiao‐Kang, et al.. (2017). Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry. Nature Biotechnology. 35(2). 164–172. 30 indexed citations

11.

Wollny, Damian, Sheng Zhao, Xiao‐Kang Lun, et al.. (2016). Single-Cell Analysis Uncovers Clonal Acinar Cell Heterogeneity in the Adult Pancreas. Developmental Cell. 39(3). 289–301. 73 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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