Chong Wu

2.8k total citations
83 papers, 1.4k citations indexed

About

Chong Wu is a scholar working on Molecular Biology, Genetics and Statistics and Probability. According to data from OpenAlex, Chong Wu has authored 83 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 37 papers in Genetics and 9 papers in Statistics and Probability. Recurrent topics in Chong Wu's work include Genetic Associations and Epidemiology (33 papers), Epigenetics and DNA Methylation (14 papers) and Bioinformatics and Genomic Networks (12 papers). Chong Wu is often cited by papers focused on Genetic Associations and Epidemiology (33 papers), Epigenetics and DNA Methylation (14 papers) and Bioinformatics and Genomic Networks (12 papers). Chong Wu collaborates with scholars based in United States, China and United Kingdom. Chong Wu's co-authors include Wei Pan, Lang Wu, Zhiyuan Xu, Jingjing Zhu, Hong‐Wen Deng, Yuan Yuan, Luqi Huang, Yunjun Liu, Yanfa Sun and Peng Wei and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Journal of the American Statistical Association.

In The Last Decade

Chong Wu

79 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chong Wu United States 20 889 372 160 143 129 83 1.4k
Scott Dudek United States 24 979 1.1× 852 2.3× 65 0.4× 88 0.6× 359 2.8× 52 2.2k
Mitchell Martin United States 13 1.2k 1.3× 575 1.5× 40 0.3× 248 1.7× 94 0.7× 19 1.9k
Danielle Welter Luxembourg 6 1.8k 2.1× 1.6k 4.4× 33 0.2× 219 1.5× 66 0.5× 12 3.2k
Peggy Hall United States 5 1.8k 2.1× 1.6k 4.4× 33 0.2× 221 1.5× 68 0.5× 8 3.3k
Jacqueline A. L. MacArthur United Kingdom 9 2.0k 2.2× 1.9k 5.1× 33 0.2× 241 1.7× 81 0.6× 13 3.7k
Habil Zare United States 15 566 0.6× 83 0.2× 46 0.3× 232 1.6× 87 0.7× 32 1.0k
Ada Piepoli Italy 26 806 0.9× 301 0.8× 84 0.5× 205 1.4× 46 0.4× 66 1.8k
Emma Hastings United Kingdom 3 1.1k 1.3× 754 2.0× 12 0.1× 128 0.9× 83 0.6× 3 1.9k
Rong Chen United States 21 840 0.9× 510 1.4× 11 0.1× 154 1.1× 76 0.6× 57 1.8k
Matthew J. Callow United States 12 1.4k 1.5× 383 1.0× 10 0.1× 86 0.6× 88 0.7× 21 1.9k

Countries citing papers authored by Chong Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chong Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chong Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chong Wu. A scholar is included among the top collaborators of Chong 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 Chong Wu. Chong 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.
Sun, Yanfa, Jingjing Zhu, Fubo Wang, et al.. (2025). Transcriptome‐Wide Association Study Identified Novel Blood Tissue Gene Biomarkers for Prostate Cancer Risk. The Prostate. 85(6). 567–579.
2.
Zhao, Bingxin, Chad D. Huff, Jianjun Zhang, et al.. (2025). Benchmarking DNA foundation models for genomic and genetic tasks. Nature Communications. 16(1). 10780–10780. 1 indexed citations
3.
Ji, Jiadong, Kuan‐Jui Su, Chuan Qiu, et al.. (2024). omicsMIC: a comprehensive benchmarking platform for robust comparison of imputation methods in mass spectrometry-based omics data. NAR Genomics and Bioinformatics. 6(2). lqae071–lqae071. 3 indexed citations
4.
Gong, Zeyu, et al.. (2024). Climb-Odom: A robust and low-drift RGB-D inertial odometry with surface continuity constraints for climbing robots on freeform surface. Information Fusion. 117. 102880–102880. 2 indexed citations
5.
Meng, Xiang‐He, Chong Wu, Kuan‐Jui Su, et al.. (2024). Variability in performance of genetic-enhanced DXA-BMD prediction models across diverse ethnic and geographic populations: A risk prediction study. PLoS Medicine. 21(8). e1004451–e1004451. 2 indexed citations
6.
Wang, Jingshen, et al.. (2024). Sensitivity analysis with iterative outlier detection for systematic reviews and meta‐analyses. Statistics in Medicine. 43(8). 1549–1563. 13 indexed citations
7.
Zhu, Jingjing, Shuai Liu, Keenan A. Walker, et al.. (2024). Associations between genetically predicted plasma protein levels and Alzheimer’s disease risk: a study using genetic prediction models. Alzheimer s Research & Therapy. 16(1). 8–8. 7 indexed citations
8.
Huang, Zhongling, Chong Wu, Xiwen Yao, et al.. (2023). Physics inspired hybrid attention for SAR target recognition. ISPRS Journal of Photogrammetry and Remote Sensing. 207. 164–174. 28 indexed citations
9.
Wu, Chong, et al.. (2023). SUMMIT-FA: a new resource for improved transcriptome imputation using functional annotations. Human Molecular Genetics. 33(7). 624–635. 1 indexed citations
10.
Liu, Duo, Jingjing Zhu, Yanfa Sun, et al.. (2023). Splicing transcriptome-wide association study to identify splicing events for pancreatic cancer risk. Carcinogenesis. 44(10-11). 741–747. 2 indexed citations
11.
Wu, Chong, Jonathan R. Bradley, Yanming Li, Lang Wu, & Hong‐Wen Deng. (2021). A gene-level methylome-wide association analysis identifies novel Alzheimer’s disease genes. Bioinformatics. 37(14). 1933–1940. 6 indexed citations
12.
Wu, Chong, Jingjing Zhu, Xiaoran Tong, et al.. (2021). Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi‐phased study of prostate cancer. Cancer Communications. 41(12). 1387–1397. 8 indexed citations
13.
Liu, Duo, Jingjing Zhu, Dan Zhou, et al.. (2021). A transcriptome‐wide association study identifies novel candidate susceptibility genes for prostate cancer risk. International Journal of Cancer. 150(1). 80–90. 18 indexed citations
14.
Liu, Duo, Dan Zhou, Yanfa Sun, et al.. (2020). A Transcriptome-Wide Association Study Identifies Candidate Susceptibility Genes for Pancreatic Cancer Risk. Cancer Research. 80(20). 4346–4354. 30 indexed citations
15.
Wu, Chong. (2020). Multi-trait Genome-Wide Analyses of the Brain Imaging Phenotypes in UK Biobank. Genetics. 215(4). 947–958. 11 indexed citations
16.
Wu, Chong, et al.. (2018). An adaptive gene-based test for methylation data. BMC Proceedings. 12(S9). 60–60. 1 indexed citations
17.
Wu, Chong, Can Yang, Hongyu Zhao, & Ji Zhu. (2016). On the Convergence of the EM Algorithm: From the Statistical Perspective. arXiv (Cornell University). 2 indexed citations
18.
Wu, Chong, Jun Chen, Junghi Kim, & Wei Pan. (2016). An adaptive association test for microbiome data. Genome Medicine. 8(1). 56–56. 55 indexed citations
19.
Wu, Chong, Han Yan, Jing Zhi Sun, et al.. (2013). NEXN Is a Novel Susceptibility Gene for Coronary Artery Disease in Han Chinese. PLoS ONE. 8(12). e82135–e82135. 17 indexed citations
20.
Cheng, Chunyan, Yuan Lin, Fan Yang, et al.. (2011). Mutational screening of affected cardiac tissues and peripheral blood cells identified novel somatic mutations in GATA4 in patients with ventricular septal defect. Journal of Biomedical Research. 25(6). 425–430. 6 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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