Chung‐I Wu

18.7k total citations · 3 hit papers
146 papers, 12.4k citations indexed

About

Chung‐I Wu is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Chung‐I Wu has authored 146 papers receiving a total of 12.4k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Genetics, 70 papers in Molecular Biology and 32 papers in Cancer Research. Recurrent topics in Chung‐I Wu's work include Genetic diversity and population structure (54 papers), Evolution and Genetic Dynamics (40 papers) and Genomics and Phylogenetic Studies (25 papers). Chung‐I Wu is often cited by papers focused on Genetic diversity and population structure (54 papers), Evolution and Genetic Dynamics (40 papers) and Genomics and Phylogenetic Studies (25 papers). Chung‐I Wu collaborates with scholars based in United States, China and Taiwan. Chung‐I Wu's co-authors include Justin C. Fay, Chau‐Ti Ting, Wen‐Hsiung Li, Gerald J. Wyckoff, Shun-Chern Tsaur, Michael F Palopoli, Suhua Shi, Norman Johnson, Wen Wang and Jian Lü and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Chung‐I Wu

143 papers receiving 12.2k citations

Hit Papers

Hitchhiking Under Positive Darwinian Selection 1985 2026 1998 2012 2000 2001 1985 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chung‐I Wu United States 53 8.1k 5.0k 3.0k 2.5k 1.5k 146 12.4k
Matthew W. Hahn United States 61 7.7k 1.0× 7.4k 1.5× 2.6k 0.9× 3.9k 1.5× 1.5k 1.0× 170 14.7k
Dmitri A. Petrov United States 69 6.8k 0.8× 8.2k 1.6× 1.4k 0.5× 4.1k 1.6× 1.3k 0.9× 193 14.4k
Christian Schlötterer Austria 65 9.7k 1.2× 6.2k 1.2× 3.0k 1.0× 3.9k 1.6× 3.5k 2.3× 240 16.7k
David L. Stern United States 51 4.3k 0.5× 4.5k 0.9× 3.0k 1.0× 1.8k 0.7× 901 0.6× 128 10.2k
Charles F. Aquadro United States 61 8.0k 1.0× 4.7k 0.9× 2.5k 0.9× 2.3k 0.9× 1.6k 1.1× 163 12.1k
Angel Amores United States 32 6.4k 0.8× 7.5k 1.5× 1.4k 0.5× 3.0k 1.2× 1.8k 1.2× 54 13.5k
Charles H. Langley United States 58 7.1k 0.9× 5.9k 1.2× 1.7k 0.6× 4.9k 2.0× 759 0.5× 140 12.3k
Laurence D. Hurst United Kingdom 69 7.0k 0.9× 12.5k 2.5× 1.9k 0.6× 3.8k 1.5× 945 0.6× 277 18.5k
Michael W. Nachman United States 63 6.7k 0.8× 3.5k 0.7× 2.3k 0.8× 1.4k 0.6× 1.8k 1.2× 137 10.7k
Martin Kreitman United States 54 7.2k 0.9× 6.9k 1.4× 1.9k 0.6× 4.7k 1.9× 1.2k 0.8× 101 14.3k

Countries citing papers authored by Chung‐I Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chung‐I Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chung‐I Wu. 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 Chung‐I Wu. The network helps show where Chung‐I Wu may publish in the future.

Co-authorship network of co-authors of Chung‐I Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chung‐I Wu. A scholar is included among the top collaborators of Chung‐I Wu 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 Chung‐I Wu. Chung‐I Wu 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.
Feng, Xiao, Guo-Hong Li, Shaohua Xu, et al.. (2024). Genomic evidence for rediploidization and adaptive evolution following the whole-genome triplication. Nature Communications. 15(1). 1635–1635. 25 indexed citations
3.
Ruan, Yongsen, Xiaolu Tang, Xionglei He, et al.. (2022). The Runaway Evolution of SARS-CoV-2 Leading to the Highly Evolved Delta Strain. Molecular Biology and Evolution. 39(3). 13 indexed citations
4.
Yang, Hao, Xiao Feng, Qingjian Chen, et al.. (2021). Two decades of suspect evidence for adaptive molecular evolution—negative selection confounding positive-selection signals. National Science Review. 9(5). nwab217–nwab217. 13 indexed citations
5.
Zhao, Shilei, Tong Sha, Chung‐I Wu, Yongbiao Xue, & Hua Chen. (2021). Will the large‐scale vaccination succeed in containing the COVID‐19 pandemic and how soon?. Quantitative Biology. 9(3). 304–316. 1 indexed citations
6.
Ruan, Yongsen, Haijun Wen, Ziwen He, et al.. (2021). The twin-beginnings of COVID-19 in Asia and Europe—one prevails quickly. National Science Review. 9(4). nwab223–nwab223. 14 indexed citations
7.
Zhao, Shilei, Tong Sha, Yongbiao Xue, Chung‐I Wu, & Hua Chen. (2021). Will the Large-Scale Vaccination Succeed in Containing the COVID-19 Pandemic and How Soon?. SSRN Electronic Journal. 2 indexed citations
8.
Chen, Qingjian, et al.. (2019). Molecular Evolution in Large Steps—Codon Substitutions under Positive Selection. Molecular Biology and Evolution. 36(9). 1862–1873. 14 indexed citations
9.
Chen, Qingjian, et al.. (2019). Molecular Evolution in Small Steps under Prevailing Negative Selection: A Nearly Universal Rule of Codon Substitution. Genome Biology and Evolution. 11(10). 2702–2712. 9 indexed citations
10.
Ruan, Yongsen, Haiyu Wang, Bingjie Chen, Haijun Wen, & Chung‐I Wu. (2019). Mutations Beget More Mutations—Rapid Evolution of Mutation Rate in Response to the Risk of Runaway Accumulation. Molecular Biology and Evolution. 37(4). 1007–1019. 8 indexed citations
11.
He, Ziwen, Xinnian Li, Ming Yang, et al.. (2018). Speciation with gene flow via cycles of isolation and migration: insights from multiple mangrove taxa. National Science Review. 6(2). 275–288. 95 indexed citations
12.
Zhao, Yixin, et al.. (2018). On the possibility of death of new genes – evidence from the deletion of de novo microRNAs. BMC Genomics. 19(1). 388–388. 4 indexed citations
13.
Zhao, Yixin, Hao Yang, Suhua Shi, et al.. (2018). Death of new microRNA genes in Drosophila via gradual loss of fitness advantages. Genome Research. 28(9). 1309–1318. 8 indexed citations
14.
Xu, Shaohua, Ziwen He, Zixiao Guo, et al.. (2017). Genome-Wide Convergence during Evolution of Mangroves from Woody Plants. Molecular Biology and Evolution. 34(4). msw277–msw277. 56 indexed citations
15.
Lyu, Yang, Heng Li, Li Guo, et al.. (2014). New MicroRNAs in Drosophila—Birth, Death and Cycles of Adaptive Evolution. PLoS Genetics. 10(1). e1004096–e1004096. 43 indexed citations
16.
Wang, Guodong, Weiwei Zhai, Hechuan Yang, et al.. (2013). The genomics of selection in dogs and the parallel evolution between dogs and humans. Nature Communications. 4(1). 1860–1860. 207 indexed citations
17.
Xu, Jin, Rui Zhang, Yang Shen, et al.. (2013). The evolution of evolvability in microRNA target sites in vertebrates. Genome Research. 23(11). 1810–1816. 46 indexed citations
18.
Alipaz, Julie, Shu Fang, Naoki Osada, & Chung‐I Wu. (2005). Evolution of Sexual Isolation during Secondary Contact: Genotypic versus Phenotypic Changes in Laboratory Populations. The American Naturalist. 165(4). 420–428. 16 indexed citations
19.
Greenberg, Anthony J., Jennifer Moran, Jerry A. Coyne, & Chung‐I Wu. (2003). Ecological Adaptation During Incipient Speciation Revealed by Precise Gene Replacement. Science. 302(5651). 1754–1757. 146 indexed citations
20.
Palopoli, Michael F, A. W. Davis, & Chung‐I Wu. (1996). Discord Between the Phylogenies Inferred From Molecular Versus Functional Data: Uneven Rates of Functional Evolution or Low Levels of Gene Flow?. Genetics. 144(3). 1321–1328. 28 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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