Kuo‐Ching Chu

642 total citations
8 papers, 360 citations indexed

About

Kuo‐Ching Chu is a scholar working on Molecular Biology, Organic Chemistry and Biotechnology. According to data from OpenAlex, Kuo‐Ching Chu has authored 8 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Organic Chemistry and 2 papers in Biotechnology. Recurrent topics in Kuo‐Ching Chu's work include Glycosylation and Glycoproteins Research (6 papers), Chemical Synthesis and Analysis (4 papers) and Carbohydrate Chemistry and Synthesis (4 papers). Kuo‐Ching Chu is often cited by papers focused on Glycosylation and Glycoproteins Research (6 papers), Chemical Synthesis and Analysis (4 papers) and Carbohydrate Chemistry and Synthesis (4 papers). Kuo‐Ching Chu collaborates with scholars based in Taiwan, United States and United Kingdom. Kuo‐Ching Chu's co-authors include Chi‐Huey Wong, Chien‐Tai Ren, Chung‐Yi Wu, Jeng‐Liang Han, Yih‐Shyan Lin, Che-hsiung Hsu, Jung‐Tung Hung, Alice L. Yu, Yen‐Lin Huang and Hsinyu Lee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Angewandte Chemie International Edition and Chemistry - A European Journal.

In The Last Decade

Kuo‐Ching Chu

8 papers receiving 359 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kuo‐Ching Chu Taiwan	6	291	259	72	39	38	8	360
Shiou‐Ting Li Taiwan	8	309 1.1×	247 1.0×	78 1.1×	47 1.2×	79 2.1×	10	397
Amberlyn M. Wands United States	12	397 1.4×	210 0.8×	95 1.3×	24 0.6×	60 1.6×	12	498
Manuel Schorlemer Germany	9	371 1.3×	170 0.7×	103 1.4×	23 0.6×	82 2.2×	12	427
Gerlof P. Bosman Netherlands	10	275 0.9×	174 0.7×	70 1.0×	31 0.8×	81 2.1×	14	343
Ian Loke Australia	12	380 1.3×	107 0.4×	190 2.6×	36 0.9×	35 0.9×	14	456
J. Castro-López Spain	10	302 1.0×	194 0.7×	68 0.9×	21 0.5×	114 3.0×	17	396
Matthias Iwersen Germany	9	294 1.0×	140 0.5×	67 0.9×	43 1.1×	35 0.9×	11	365
Jérémy Boilevin Switzerland	9	375 1.3×	144 0.6×	62 0.9×	26 0.7×	25 0.7×	10	459
Yih‐Shyan Lin Canada	10	333 1.1×	292 1.1×	26 0.4×	25 0.6×	34 0.9×	13	431
Chang‐Xin Huo China	12	346 1.2×	280 1.1×	75 1.0×	40 1.0×	87 2.3×	18	418

Countries citing papers authored by Kuo‐Ching Chu

Since Specialization

Citations

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

Fields of papers citing papers by Kuo‐Ching Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuo‐Ching Chu. 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 Kuo‐Ching Chu. The network helps show where Kuo‐Ching Chu may publish in the future.

Co-authorship network of co-authors of Kuo‐Ching Chu

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

All Works

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8 of 8 papers shown

1.

Chuang, Hong-Yang, Chiu-Chen Huang, Lin‐Ya Huang, et al.. (2021). Development of biotinylated and magnetic bead-immobilized enzymes for efficient glyco-engineering and isolation of antibodies. Bioorganic Chemistry. 112. 104863–104863. 4 indexed citations

2.

Wu, Ying‐Ta, Jingrong Huang, Jung‐Tung Hung, et al.. (2016). Phenyl Glycolipids with Different Glycosyl Groups Exhibit Marked Differences in Murine and Human iNKT Cell Activation. ACS Chemical Biology. 11(12). 3431–3441. 14 indexed citations

3.

Huang, Yen‐Lin, Jung‐Tung Hung, Hsinyu Lee, et al.. (2013). Carbohydrate-based vaccines with a glycolipid adjuvant for breast cancer. Proceedings of the National Academy of Sciences. 110(7). 2517–2522. 127 indexed citations

4.

Chu, Kuo‐Ching, Chien‐Tai Ren, Chun‐Ping Lu, et al.. (2011). Efficient and Stereoselective Synthesis of α(2→9) Oligosialic Acids: From Monomers to Dodecamers. Angewandte Chemie International Edition. 50(40). 9391–9395. 57 indexed citations

5.

Chu, Kuo‐Ching, Chien‐Tai Ren, Chun‐Ping Lu, et al.. (2011). Efficient and Stereoselective Synthesis of α(2→9) Oligosialic Acids: From Monomers to Dodecamers. Angewandte Chemie. 123(40). 9563–9567. 12 indexed citations

6.

Hsu, Che-hsiung, Kuo‐Ching Chu, Yih‐Shyan Lin, et al.. (2010). Highly Alpha‐Selective Sialyl Phosphate Donors for Efficient Preparation of Natural Sialosides. Chemistry - A European Journal. 16(6). 1754–1760. 139 indexed citations

7.

Liu, Hsing‐Jang, Jia‐Liang Zhu, & Kuo‐Ching Chu. (2010). A New and Efficient Total Synthesis of (±)-Laurencenone C. Synlett. 2010(20). 3061–3064. 5 indexed citations

8.

Hsu, Che‐Hsiung, Kuo‐Ching Chu, Yih‐Shyan Lin, et al.. (2010). ChemInform Abstract: Highly α‐Selective Sialyl Phosphate Donors for Efficient Preparation of Natural Sialosides.. ChemInform. 41(21). 2 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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