Kuo‐Chang Yin

1.8k total citations · 1 hit paper
15 papers, 1.6k citations indexed

About

Kuo‐Chang Yin is a scholar working on Molecular Biology, Oncology and Physiology. According to data from OpenAlex, Kuo‐Chang Yin has authored 15 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Oncology and 3 papers in Physiology. Recurrent topics in Kuo‐Chang Yin's work include Alzheimer's disease research and treatments (3 papers), RNA regulation and disease (2 papers) and Biosimilars and Bioanalytical Methods (2 papers). Kuo‐Chang Yin is often cited by papers focused on Alzheimer's disease research and treatments (3 papers), RNA regulation and disease (2 papers) and Biosimilars and Bioanalytical Methods (2 papers). Kuo‐Chang Yin collaborates with scholars based in United States, China and United Kingdom. Kuo‐Chang Yin's co-authors include Xiao‐Ping Shi, Stephen J. Gardell, Yue‐Ming Li, Ming‐Tain Lai, Mohinder K. Sardana, Jules A. Shafer, Qian Huang, Min Xu, R B Register and José L. Castro and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Kuo‐Chang Yin

15 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Photoactivated γ-secretase inhibitors directed to the active site covalently label presenilin 1

2000 738 citations Yue‐Ming Li, Min Xu et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kuo‐Chang Yin United States	10	1.0k	883	370	282	238	15	1.6k
Xiao‐Ping Shi United States	20	1.4k 1.3×	1.2k 1.4×	591 1.6×	342 1.2×	372 1.6×	42	2.2k
Akio Fukumori Germany	27	1.1k 1.0×	974 1.1×	357 1.0×	328 1.2×	324 1.4×	49	1.9k
Helmut Romig Germany	17	1.1k 1.1×	1.1k 1.2×	337 0.9×	381 1.4×	129 0.5×	23	1.8k
Adele M. Pauley United States	10	1.1k 1.1×	1.2k 1.4×	496 1.3×	277 1.0×	342 1.4×	11	2.0k
Mary F. Knauer United States	13	1.2k 1.2×	798 0.9×	273 0.7×	195 0.7×	240 1.0×	16	1.6k
Debra Burdick United States	8	1.2k 1.2×	683 0.8×	243 0.7×	97 0.3×	227 1.0×	10	1.5k
Audrey A. Darabie Canada	14	1.1k 1.1×	782 0.9×	260 0.7×	173 0.6×	261 1.1×	16	1.5k
Dana Kim Reed United States	18	814 0.8×	689 0.8×	177 0.5×	191 0.7×	178 0.7×	21	1.3k
Kulandaivelu S. Vetrivel United States	21	1.5k 1.5×	1.2k 1.3×	305 0.8×	532 1.9×	171 0.7×	25	2.1k
Sanjiv Shah United States	12	652 0.6×	591 0.7×	201 0.5×	247 0.9×	117 0.5×	16	1.0k

Countries citing papers authored by Kuo‐Chang Yin

Since Specialization

Citations

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

Fields of papers citing papers by Kuo‐Chang Yin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kuo‐Chang Yin

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

All Works

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15 of 15 papers shown

Xu, Guodong, et al.. (2023). Evaluation of safety and efficacy of rapamycin-eluting balloon in patients with intracranial atherosclerotic stenosis: a cohort study. Journal of Cardiothoracic Surgery. 18(1). 2 indexed citations

Zhou, Yi, Bin Li, Shan Wang, et al.. (2018). Expression of Bcl-2 and Bad in hippocampus of status epileptic rats and molecular mechanism of intervened recombinant human erythropoietin. Experimental and Therapeutic Medicine. 16(2). 847–855. 8 indexed citations

Wang, Weirong, Nancy Chen, Xiaolan Shen, et al.. (2012). Lymphatic Transport and Catabolism of Therapeutic Proteins after Subcutaneous Administration to Rats and Dogs. Drug Metabolism and Disposition. 40(5). 952–962. 69 indexed citations

Liu, Li, et al.. (2012). The Impact of Sialic Acids on the Pharmacokinetics of a PEGylated Erythropoietin. Journal of Pharmaceutical Sciences. 101(12). 4414–4418. 9 indexed citations

Yin, Kuo‐Chang, et al.. (2011). Evaluation of Two ELISA Methods to Detect Therapeutic Anti-IGF1R Antibodies in Clinical Study Samples of Dalotuzumab. Bioanalysis. 3(18). 2107–2117. 1 indexed citations

Verch, Thorsten, et al.. (2010). Pharmacokinetic immunoassay methods in the presence of soluble target. Journal of Immunological Methods. 361(1-2). 75–81. 14 indexed citations

Morris, Michael L., et al.. (2003). Development and implementation of an electrochemiluminescence immunoassay for the determination of an angiogenic polypeptide in dog and rat plasma. Journal of Pharmaceutical and Biomedical Analysis. 33(4). 719–724. 2 indexed citations

Shi, Xiao‐Ping, Elizabeth Chen, Kuo‐Chang Yin, et al.. (2001). The Pro Domain of β-Secretase Does Not Confer Strict Zymogen-like Properties but Does Assist Proper Folding of the Protease Domain. Journal of Biological Chemistry. 276(13). 10366–10373. 104 indexed citations

Li, Yue‐Ming, Min Xu, Ming‐Tain Lai, et al.. (2000). Photoactivated γ-secretase inhibitors directed to the active site covalently label presenilin 1. Nature. 405(6787). 689–694. 738 indexed citations breakdown →

10.

Li, Yue‐Ming, Ming‐Tain Lai, Min Xu, et al.. (2000). Presenilin 1 is linked with γ-secretase activity in the detergent solubilized state. Neurobiology of Aging. 21. 277–277. 4 indexed citations

11.

Li, Yue‐Ming, Ming‐Tain Lai, Min Xu, et al.. (2000). Presenilin 1 is linked with γ-secretase activity in the detergent solubilized state. Proceedings of the National Academy of Sciences. 97(11). 6138–6143. 462 indexed citations

12.

Shi, Xiao‐Ping, Kuo‐Chang Yin, & Lloyd Waxman. (1997). Effects of Inhibitors of RNA and Protein Synthesis on the Subcellular Distribution of the Eukaryotic Translation Initiation Factor, eIF-5A, and the HIV-1 Rev Protein. Neurosignals. 6(3). 143–149. 21 indexed citations

13.

Shi, Xiao‐Ping, et al.. (1996). Effects of N1-guanyl-1,7-diaminoheptane, an inhibitor of deoxyhypusine synthase, on the growth of tumorigenic cell lines in culture. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1310(1). 119–126. 62 indexed citations

14.

Shi, Xiao‐Ping, Kuo‐Chang Yin, Zoran Zimolo, Andrew M. Stern, & Lloyd Waxman. (1996). The Subcellular Distribution of Eukaryotic Translation Initiation Factor, eIF-5A, in Cultured Cells. Experimental Cell Research. 225(2). 348–356. 41 indexed citations

15.

Shi, Xiao‐Ping, Kuo‐Chang Yin, & Stephen J. Gardell. (1995). Human erythroleukemic (HEL) cells express a platelet P2T-like ADP receptor. Thrombosis Research. 77(3). 235–247. 19 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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