Qiang Kou

876 total citations
21 papers, 687 citations indexed

About

Qiang Kou is a scholar working on Spectroscopy, Molecular Biology and Media Technology. According to data from OpenAlex, Qiang Kou has authored 21 papers receiving a total of 687 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Spectroscopy, 12 papers in Molecular Biology and 2 papers in Media Technology. Recurrent topics in Qiang Kou's work include Advanced Proteomics Techniques and Applications (16 papers), Mass Spectrometry Techniques and Applications (16 papers) and Metabolomics and Mass Spectrometry Studies (9 papers). Qiang Kou is often cited by papers focused on Advanced Proteomics Techniques and Applications (16 papers), Mass Spectrometry Techniques and Applications (16 papers) and Metabolomics and Mass Spectrometry Studies (9 papers). Qiang Kou collaborates with scholars based in United States, China and Chile. Qiang Kou's co-authors include Xiaowen Liu, Liangliang Sun, Xiaojing Shen, Rachele A. Lubeckyj, Elijah N. McCool, Si Wu, Daoyang Chen, Ljiljana Paša‐Tolić, Nikola Tolić and Heedeok Hong and has published in prestigious journals such as Bioinformatics, Analytical Chemistry and BMC Bioinformatics.

In The Last Decade

Qiang Kou

21 papers receiving 681 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qiang Kou United States 12 533 401 147 29 22 21 687
Lissa C. Anderson United States 18 551 1.0× 485 1.2× 74 0.5× 18 0.6× 51 2.3× 34 869
Matthew B. O’Rourke Australia 11 183 0.3× 218 0.5× 55 0.4× 21 0.7× 10 0.5× 28 417
Steven J. Rysavy United States 7 98 0.2× 338 0.8× 41 0.3× 19 0.7× 39 1.8× 10 514
Michael C. Giddings United States 11 48 0.1× 259 0.6× 56 0.4× 26 0.9× 4 0.2× 14 374
Getiria Onsongo United States 13 248 0.5× 407 1.0× 28 0.2× 90 3.1× 11 0.5× 22 703
Sophia Steigerwald Denmark 4 219 0.4× 257 0.6× 22 0.1× 13 0.4× 8 0.4× 10 360
Bachir El Debs Germany 3 35 0.1× 157 0.4× 386 2.6× 7 0.2× 38 1.7× 4 513
Maria Hammond Sweden 10 46 0.1× 307 0.8× 134 0.9× 25 0.9× 58 2.6× 17 422
P.F. Lemkin United States 9 156 0.3× 270 0.7× 38 0.3× 15 0.5× 17 0.8× 17 379
Lajos Nyársik Germany 7 40 0.1× 260 0.6× 133 0.9× 26 0.9× 55 2.5× 14 366

Countries citing papers authored by Qiang Kou

Since Specialization
Citations

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

Fields of papers citing papers by Qiang Kou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiang Kou

This figure shows the co-authorship network connecting the top 25 collaborators of Qiang Kou. A scholar is included among the top collaborators of Qiang Kou 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 Qiang Kou. Qiang Kou 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.
Wang, Zhe, Kellye A. Cupp‐Sutton, Yanting Guo, et al.. (2021). Quantitative Top-Down Proteomics in Complex Samples Using Protein-Level Tandem Mass Tag Labeling. Journal of the American Society for Mass Spectrometry. 32(6). 1336–1344. 41 indexed citations
2.
McCool, Elijah N., Rachele A. Lubeckyj, Xiaojing Shen, et al.. (2018). Deep Top-Down Proteomics Using Capillary Zone Electrophoresis-Tandem Mass Spectrometry: Identification of 5700 Proteoforms from the Escherichia coli Proteome. PMC. 5 indexed citations
3.
McCool, Elijah N., Rachele A. Lubeckyj, Xiaojing Shen, et al.. (2018). Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry. Journal of Visualized Experiments. 23 indexed citations
4.
He, Bo, Qiang Kou, Zhe Wang, et al.. (2018). Evaluation of top-down mass spectral identification with homologous protein sequences. BMC Bioinformatics. 19(S17). 494–494. 4 indexed citations
5.
Kou, Qiang, Si Wu, & Xiaowen Liu. (2018). Systematic Evaluation of Protein Sequence Filtering Algorithms for Proteoform Identification Using Top‐Down Mass Spectrometry. PROTEOMICS. 18(3-4). 9 indexed citations
6.
McCool, Elijah N., et al.. (2018). Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry. Journal of Visualized Experiments. 4 indexed citations
7.
McCool, Elijah N., Rachele A. Lubeckyj, Xiaojing Shen, et al.. (2018). Deep Top-Down Proteomics Using Capillary Zone Electrophoresis-Tandem Mass Spectrometry: Identification of 5700 Proteoforms from the Escherichia coli Proteome. Analytical Chemistry. 90(9). 5529–5533. 93 indexed citations
8.
Shen, Xiaojing, Qiang Kou, Zhichang Yang, et al.. (2018). Native Proteomics in Discovery Mode Using Size-Exclusion Chromatography–Capillary Zone Electrophoresis–Tandem Mass Spectrometry. Analytical Chemistry. 90(17). 10095–10099. 65 indexed citations
9.
Liu, Tao, et al.. (2017). [Physical fingerprint for quality control of Reduning injection].. PubMed. 42(3). 505–509. 2 indexed citations
10.
Kou, Qiang, Si Wu, Nikola Tolić, et al.. (2017). A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra. PMC. 1 indexed citations
11.
Zhu, Daming, Qiang Kou, Poornima Bhat‐Nakshatri, et al.. (2017). A spectrum graph-based protein sequence filtering algorithm for proteoform identification by top-down mass spectrometry. PubMed. 2017. 222–229. 2 indexed citations
12.
Lubeckyj, Rachele A., Elijah N. McCool, Xiaojing Shen, et al.. (2017). Single-Shot Top-Down Proteomics with Capillary Zone Electrophoresis-Electrospray Ionization-Tandem Mass Spectrometry for Identification of Nearly 600 Escherichia coli Proteoforms. Analytical Chemistry. 89(22). 12059–12067. 81 indexed citations
13.
Kou, Qiang, et al.. (2016). TopPIC: a software tool for top-down mass spectrometry-based proteoform identification and characterization. Bioinformatics. 32(22). 3495–3497. 209 indexed citations
14.
Kou, Qiang, Binhai Zhu, Si Wu, et al.. (2016). Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore. Journal of Proteome Research. 15(8). 2422–2432. 18 indexed citations
15.
Kou, Qiang, Si Wu, Nikola Tolić, et al.. (2016). A mass graph-based approach for the identification of modified proteoforms using top-down tandem mass spectra. Bioinformatics. 33(9). 1309–1316. 32 indexed citations
16.
17.
Kou, Qiang, et al.. (2015). Single-sample SNP detection by empirical Bayes method using next-generation sequencing data. Statistics and Its Interface. 8(4). 457–462. 1 indexed citations
18.
Dündar, Murat, et al.. (2015). Simplicity of Kmeans Versus Deepness of Deep Learning: A Case of Unsupervised Feature Learning with Limited Data. IUScholarWorks (Indiana University). 883–888. 15 indexed citations
19.
Kou, Qiang, Si Wu, & Xiaowen Liu. (2014). A new scoring function for top-down spectral deconvolution. BMC Genomics. 15(1). 1140–1140. 14 indexed citations
20.
Liu, Xiaowen, Lennard J. M. Dekker, Si Wu, et al.. (2014). De Novo Protein Sequencing by Combining Top-Down and Bottom-Up Tandem Mass Spectra. Journal of Proteome Research. 13(7). 3241–3248. 51 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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