Wanjun Gu

7.7k total citations · 1 hit paper
60 papers, 3.1k citations indexed

About

Wanjun Gu is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Wanjun Gu has authored 60 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 21 papers in Cancer Research and 9 papers in Genetics. Recurrent topics in Wanjun Gu's work include RNA and protein synthesis mechanisms (20 papers), Genomics and Phylogenetic Studies (18 papers) and MicroRNA in disease regulation (15 papers). Wanjun Gu is often cited by papers focused on RNA and protein synthesis mechanisms (20 papers), Genomics and Phylogenetic Studies (18 papers) and MicroRNA in disease regulation (15 papers). Wanjun Gu collaborates with scholars based in China, United States and South Korea. Wanjun Gu's co-authors include Tong Zhou, David D. Pollock, Todd A. Castoe, A. P. Jason de Koning, Mark A. Batzer, Zuhong Lu, Claus O. Wilke, Xiao Sun, Jianmin Ma and Jae-Hong Ko and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and PLoS ONE.

In The Last Decade

Wanjun Gu

58 papers receiving 3.1k citations

Hit Papers

Repetitive Elements May Comprise Over Two-Thirds of the H... 2011 2026 2016 2021 2011 250 500 750
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.

  1. Repetitive Elements May Comprise Over Two-Thirds of the Human Genome
    2011 787 citations A. P. Jason de Koning, Wanjun Gu et al. PLoS Genetics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wanjun Gu China 25 2.5k 698 645 616 223 60 3.1k
Kathryn M. Robinson Sweden 20 1.9k 0.7× 533 0.8× 775 1.2× 430 0.7× 123 0.6× 36 2.8k
David Roazen United States 2 2.1k 0.8× 609 0.9× 617 1.0× 1.8k 2.9× 242 1.1× 2 4.3k
Albert J. Vilella United Kingdom 10 2.1k 0.8× 661 0.9× 314 0.5× 886 1.4× 190 0.9× 11 3.1k
Khalid Shakir United States 2 2.1k 0.8× 612 0.9× 626 1.0× 1.8k 3.0× 243 1.1× 2 4.3k
Alexandre Melnikov United States 17 3.1k 1.2× 614 0.9× 369 0.6× 1.0k 1.7× 152 0.7× 19 4.0k
Wojciech Makałowski Germany 33 3.1k 1.2× 1.3k 1.9× 279 0.4× 701 1.1× 168 0.8× 111 4.0k
Isaäc J. Nijman Netherlands 36 2.6k 1.0× 549 0.8× 633 1.0× 1.9k 3.0× 299 1.3× 81 5.1k
Charles G. Danko United States 30 3.5k 1.4× 344 0.5× 707 1.1× 806 1.3× 117 0.5× 69 4.4k
Mauricio O. Carneiro United States 6 2.6k 1.0× 754 1.1× 694 1.1× 2.0k 3.2× 326 1.5× 6 5.0k
Erwin L. van Dijk France 11 1.8k 0.7× 438 0.6× 412 0.6× 423 0.7× 296 1.3× 15 2.5k

Countries citing papers authored by Wanjun Gu

Since Specialization
Citations

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

Fields of papers citing papers by Wanjun Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wanjun Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Wanjun Gu. A scholar is included among the top collaborators of Wanjun Gu 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 Wanjun Gu. Wanjun Gu 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.
Gu, Wanjun, et al.. (2025). NeuronMerge: Merging Models via Functional Neuron Groups. 9015–9037.
2.
Bai, Xue, et al.. (2025). AQUARIUM_HB: a bioinformatics pipeline for human blood circular RNA analysis. Non-coding RNA Research. 16. 32–39. 1 indexed citations
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Li, Fu‐Yu, Yanhui Zhu, Yunfei Bai, et al.. (2022). Predicting hormone receptors and PAM50 subtypes of breast cancer from multi-scale lesion images of DCE-MRI with transfer learning technique. Computers in Biology and Medicine. 150. 106147–106147. 11 indexed citations
7.
Xie, Xueying, Junchao Shi, Wenjun He, et al.. (2020). Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma. Genomics Proteomics & Bioinformatics. 18(4). 468–480. 23 indexed citations
8.
Wen, Guoxia, Tong Zhou, & Wanjun Gu. (2020). The potential of using blood circular RNA as liquid biopsy biomarker for human diseases. Protein & Cell. 12(12). 911–946. 130 indexed citations
9.
Bai, Yunfei, et al.. (2019). Technical progress in circulating tumor DNA analysis using next generation sequencing. Molecular and Cellular Probes. 49. 101480–101480. 20 indexed citations
10.
Zhou, Tong, Xueying Xie, Musheng Li, et al.. (2018). Rat BodyMap transcriptomes reveal unique circular RNA features across tissue types and developmental stages. RNA. 24(11). 1443–1456. 54 indexed citations
11.
Chen, Jianle, Yun Jiang, Buqing Ni, et al.. (2017). Identification of circular RNAs in human aortic valves. Gene. 642. 135–144. 14 indexed citations
12.
Qian, Zhongqing, Hui Liu, Musheng Li, et al.. (2017). Potential Diagnostic Power of Blood Circular RNA Expression in Active Pulmonary Tuberculosis. EBioMedicine. 27. 18–26. 68 indexed citations
13.
Ko, Jae-Hong, Eun‐A Ko, Wanjun Gu, et al.. (2013). Expression profiling of ion channel genes predicts clinical outcome in breast cancer. Molecular Cancer. 12(1). 106–106. 81 indexed citations
14.
Gu, Wanjun, et al.. (2012). Selection on Synonymous Sites for Increased Accessibility around miRNA Binding Sites in Plants. Molecular Biology and Evolution. 29(10). 3037–3044. 49 indexed citations
15.
Koning, A. P. Jason de, Wanjun Gu, Todd A. Castoe, Mark A. Batzer, & David D. Pollock. (2011). Repetitive Elements May Comprise Over Two-Thirds of the Human Genome. PLoS Genetics. 7(12). e1002384–e1002384. 787 indexed citations breakdown →
16.
Guo, Li, Qi Yang, Jiafeng Lu, et al.. (2011). A Comprehensive Survey of miRNA Repertoire and 3′ Addition Events in the Placentas of Patients with Pre-Eclampsia from High-Throughput Sequencing. PLoS ONE. 6(6). e21072–e21072. 83 indexed citations
17.
Gu, Wanjun, Tong Zhou, & Claus O. Wilke. (2010). A Universal Trend of Reduced mRNA Stability near the Translation-Initiation Site in Prokaryotes and Eukaryotes. PLoS Computational Biology. 6(2). e1000664–e1000664. 242 indexed citations
18.
Castoe, Todd A., Wanjun Gu, A. P. Jason de Koning, et al.. (2009). Dynamic Nucleotide Mutation Gradients and Control Region Usage in Squamate Reptile Mitochondrial Genomes. Cytogenetic and Genome Research. 127(2-4). 112–127. 17 indexed citations
19.
Gu, Wanjun, David A. Ray, Jerilyn A. Walker, et al.. (2007). SINEs, evolution and genome structure in the opossum. Gene. 396(1). 46–58. 12 indexed citations
20.
Gu, Wanjun, Tong Zhou, Jianmin Ma, Xiao Sun, & Zuhong Lu. (2004). The relationship between synonymous codon usage and protein structure in Escherichia coli and Homo sapiens. Biosystems. 73(2). 89–97. 99 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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