Kun Huang

692 total citations
37 papers, 493 citations indexed

About

Kun Huang is a scholar working on Molecular Biology, Organic Chemistry and Biotechnology. According to data from OpenAlex, Kun Huang has authored 37 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 21 papers in Organic Chemistry and 6 papers in Biotechnology. Recurrent topics in Kun Huang's work include Glycosylation and Glycoproteins Research (22 papers), Carbohydrate Chemistry and Synthesis (17 papers) and Enzyme Production and Characterization (6 papers). Kun Huang is often cited by papers focused on Glycosylation and Glycoproteins Research (22 papers), Carbohydrate Chemistry and Synthesis (17 papers) and Enzyme Production and Characterization (6 papers). Kun Huang collaborates with scholars based in United Kingdom, China and Czechia. Kun Huang's co-authors include Sabine L. Flitsch, Peter Both, Josef Voglmeir, Li Liu, William R. Birmingham, Fabio Parmeggiani, Xiaohua Chen, Baptiste Thomas, Binbin Fan and Aiping Hu and has published in prestigious journals such as Angewandte Chemie International Edition, Analytical Chemistry and Biochemistry.

In The Last Decade

Kun Huang

36 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kun Huang United Kingdom 13 300 201 90 73 52 37 493
Yoshiki Oda Japan 13 201 0.7× 214 1.1× 81 0.9× 13 0.2× 40 0.8× 56 428
Yong‐Uk Kwon South Korea 15 340 1.1× 122 0.6× 91 1.0× 36 0.5× 40 0.8× 21 559
Oliver E. Hutt Australia 15 153 0.5× 245 1.2× 150 1.7× 38 0.5× 102 2.0× 43 618
María L. Villalonga Cuba 16 323 1.1× 72 0.4× 113 1.3× 16 0.2× 56 1.1× 19 495
David Benito‐Alifonso United Kingdom 14 340 1.1× 302 1.5× 75 0.8× 27 0.4× 290 5.6× 19 686
Guoqing Ying China 12 229 0.8× 55 0.3× 16 0.2× 37 0.5× 41 0.8× 48 483
N. Sridevi India 11 149 0.5× 75 0.4× 32 0.4× 14 0.2× 80 1.5× 20 402
Ladislav Petruš Slovakia 16 341 1.1× 341 1.7× 32 0.4× 10 0.1× 49 0.9× 54 603
Dragos Peptanariu Romania 15 129 0.4× 106 0.5× 25 0.3× 16 0.2× 111 2.1× 34 521

Countries citing papers authored by Kun Huang

Since Specialization
Citations

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

Fields of papers citing papers by Kun Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Huang. A scholar is included among the top collaborators of Kun Huang 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 Kun Huang. Kun Huang 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.
Dong, Mingyue, Wanjun Long, Hai‐Long Wu, et al.. (2024). Lightweight spatial pyramid pooling convolutional neural network assisted hyperspectral imaging for Hangbaiju origin identification. Microchemical Journal. 208. 112352–112352. 1 indexed citations
2.
Dong, Mingyue, et al.. (2023). PARAFACM: A second-order calibration algorithm for handling data with missing values. Chemometrics and Intelligent Laboratory Systems. 244. 105030–105030. 1 indexed citations
3.
Dong, Mingyue, Hai‐Long Wu, Tong Wang, Kun Huang, & Ru‐Qin Yu. (2023). A novel second-order calibration algorithm for processing fluorescence data with scattering: Three-direction resection ATLD. Chemometrics and Intelligent Laboratory Systems. 237. 104823–104823. 4 indexed citations
4.
5.
Parmeggiani, Fabio, Ryan Williams, Peter Both, et al.. (2021). A promiscuous glycosyltransferase generates poly-β-1,4-glucan derivatives that facilitate mass spectrometry-based detection of cellulolytic enzymes. Organic & Biomolecular Chemistry. 19(25). 5529–5533. 8 indexed citations
6.
Parmeggiani, Fabio, et al.. (2020). Enzymatic Building‐Block Synthesis for Solid‐Phase Automated Glycan Assembly. Angewandte Chemie. 132(50). 22642–22645. 2 indexed citations
7.
Parmeggiani, Fabio, et al.. (2020). Enzymatic Building‐Block Synthesis for Solid‐Phase Automated Glycan Assembly. Angewandte Chemie International Edition. 59(50). 22456–22459. 6 indexed citations
8.
Huang, Kun, Peter Both, Simon J. Charnock, et al.. (2020). Biochemical characterisation of an α1,4 galactosyltransferase from Neisseria weaveri for the synthesis of α1,4-linked galactosides. Organic & Biomolecular Chemistry. 18(16). 3142–3148. 9 indexed citations
9.
Valverde, Pablo, Kun Huang, Mark E. Light, et al.. (2020). Chemoenzymatic synthesis of 3-deoxy-3-fluoro-l-fucose and its enzymatic incorporation into glycoconjugates. Chemical Communications. 56(47). 6408–6411. 12 indexed citations
10.
Huang, Kun, Peter Both, Graham P. Stafford, et al.. (2020). Biocatalytic Transfer of Pseudaminic Acid (Pse5Ac7Ac) Using Promiscuous Sialyltransferases in a Chemoenzymatic Approach to Pse5Ac7Ac-Containing Glycosides. ACS Catalysis. 10(17). 9986–9993. 12 indexed citations
11.
Huang, Kun, Peter Both, Christopher Gray, et al.. (2019). Exploiting the Disialyl Galactose Activity of α2,6-Sialyltransferase from Photobacterium damselae To Generate a Highly Sialylated Recombinant α-1-Antitrypsin. Biochemistry. 59(34). 3123–3128. 8 indexed citations
12.
Huang, Kun, Fabio Parmeggiani, Peter Both, et al.. (2019). Enzymatic synthesis of N-acetyllactosamine from lactose enabled by recombinant β1,4-galactosyltransferases. Organic & Biomolecular Chemistry. 17(24). 5920–5924. 13 indexed citations
13.
Laborda, Pedro, Fabio Parmeggiani, Ai‐Min Lu, et al.. (2019). An Enzymatic N‐Acylation Step Enables the Biocatalytic Synthesis of Unnatural Sialosides. Angewandte Chemie International Edition. 59(13). 5308–5311. 13 indexed citations
14.
Laborda, Pedro, Fabio Parmeggiani, Ai‐Min Lu, et al.. (2019). An Enzymatic N‐Acylation Step Enables the Biocatalytic Synthesis of Unnatural Sialosides. Angewandte Chemie. 132(13). 5346–5349. 5 indexed citations
15.
Birmingham, William R., Peter Both, Kun Huang, et al.. (2019). Selective Oxidation of N-Glycolylneuraminic Acid Using an Engineered Galactose Oxidase Variant. ACS Catalysis. 9(9). 8208–8212. 17 indexed citations
16.
Segarra‐Maset, Maria Dolores, Kun Huang, Peter Both, et al.. (2018). ‘One-pot’ sequential enzymatic modification of synthetic glycolipids in vesicle membranes. Chemical Communications. 54(11). 1347–1350. 12 indexed citations
17.
Gray, Christopher, Antonio Sánchez‐Ruiz, Yassir Ahmed, et al.. (2017). Label-Free Discovery Array Platform for the Characterization of Glycan Binding Proteins and Glycoproteins. Analytical Chemistry. 89(8). 4444–4451. 16 indexed citations
18.
19.
Huang, Kun, Anna Kulinich, Hong Yao, et al.. (2015). Biochemical characterisation of the neuraminidase pool of the human gut symbiont Akkermansia muciniphila. Carbohydrate Research. 415. 60–65. 65 indexed citations
20.
Jiang, Guo‐Fang, et al.. (2002). Studies on genetic variations and phylogenetic relationships among five species of Tetrix using RAPD markers. 45(4). 499–502. 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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