Dewu Liu

2.7k total citations
117 papers, 1.7k citations indexed

About

Dewu Liu is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Dewu Liu has authored 117 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 47 papers in Genetics and 31 papers in Cancer Research. Recurrent topics in Dewu Liu's work include Cancer-related molecular mechanisms research (27 papers), Genetic and phenotypic traits in livestock (26 papers) and Animal Genetics and Reproduction (19 papers). Dewu Liu is often cited by papers focused on Cancer-related molecular mechanisms research (27 papers), Genetic and phenotypic traits in livestock (26 papers) and Animal Genetics and Reproduction (19 papers). Dewu Liu collaborates with scholars based in China, United States and Japan. Dewu Liu's co-authors include Zhenfang Wu, Yaokun Li, Zicong Li, Baoli Sun, Guangbin Liu, Yongqing Guo, Gengyuan Cai, Ming Deng, Junsong Shi and Enqin Zheng and has published in prestigious journals such as PLoS ONE, Journal of Agricultural and Food Chemistry and Scientific Reports.

In The Last Decade

Dewu Liu

113 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dewu Liu China 22 911 699 334 250 244 117 1.7k
Gengyuan Cai China 21 727 0.8× 728 1.0× 347 1.0× 149 0.6× 332 1.4× 127 1.6k
Mohammadreza Mohammadabadi Iran 31 654 0.7× 1.1k 1.6× 337 1.0× 357 1.4× 464 1.9× 98 2.1k
Enqin Zheng China 18 590 0.6× 552 0.8× 323 1.0× 122 0.5× 246 1.0× 93 1.2k
M.F.W. te Pas Netherlands 29 865 0.9× 1.1k 1.6× 279 0.8× 271 1.1× 914 3.7× 104 2.5k
Chandra S. Pareek Poland 14 576 0.6× 385 0.6× 213 0.6× 136 0.5× 123 0.5× 74 1.3k
Nazir Ahmad Ganai India 17 406 0.4× 332 0.5× 302 0.9× 189 0.8× 123 0.5× 119 1.1k
Ronald M. Brunner Germany 21 538 0.6× 510 0.7× 219 0.7× 494 2.0× 168 0.7× 81 1.7k
Manishi Mukesh India 23 546 0.6× 855 1.2× 206 0.6× 484 1.9× 352 1.4× 124 1.6k
Amanda K. Lindholm‐Perry United States 19 270 0.3× 688 1.0× 224 0.7× 337 1.3× 228 0.9× 77 1.2k
Ruihua Huang China 22 963 1.1× 329 0.5× 258 0.8× 121 0.5× 468 1.9× 87 1.7k

Countries citing papers authored by Dewu Liu

Since Specialization
Citations

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

Fields of papers citing papers by Dewu Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dewu Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Dewu Liu. A scholar is included among the top collaborators of Dewu Liu 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 Dewu Liu. Dewu Liu 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.
Tian, Yan, et al.. (2024). Global proteomic analysis reveals lysine succinylation is involved in the pathogenesis of hypertrophic scar. Journal of Proteomics. 298. 105155–105155. 1 indexed citations
2.
Li, Yaokun, et al.. (2024). miR-128-3p Regulates Follicular Granulosa Cell Proliferation and Apoptosis by Targeting the Growth Hormone Secretagogue Receptor. International Journal of Molecular Sciences. 25(5). 2720–2720. 3 indexed citations
3.
Liu, Jie, Conghui Guo, Junjie Fu, et al.. (2024). Identification and Functional Analysis of circRNAs during Goat Follicular Development. International Journal of Molecular Sciences. 25(14). 7548–7548. 4 indexed citations
4.
Fu, Junjie, Jie Liu, Xian Zou, et al.. (2024). Transcriptome analysis of mRNA and miRNA in the development of LeiZhou goat muscles. Scientific Reports. 14(1). 3 indexed citations
5.
Li, Yaokun, et al.. (2024). Selection and Regulatory Network Analysis of Differential CircRNAs in the Hypothalamus of Goats with High and Low Reproductive Capacity. International Journal of Molecular Sciences. 25(19). 10479–10479. 1 indexed citations
6.
Hong, Linjun, Qun Hu, Yanjuan He, et al.. (2023). Uterine luminal-derived extracellular vesicles: potential nanomaterials to improve embryo implantation. Journal of Nanobiotechnology. 21(1). 79–79. 9 indexed citations
7.
Wu, Zibin, Yongqing Guo, Jiahao Zhang, et al.. (2023). High-Dose Vitamin E Supplementation Can Alleviate the Negative Effect of Subacute Ruminal Acidosis in Dairy Cows. Animals. 13(3). 486–486. 6 indexed citations
8.
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10.
Zou, Xian, Ming Deng, Baoli Sun, et al.. (2023). Identification of Key Functional Genes and LncRNAs Influencing Muscle Growth and Development in Leizhou Black Goats. Genes. 14(4). 881–881. 5 indexed citations
11.
Liu, Jianying, Yaokun Li, Yongqing Guo, et al.. (2023). A Study on Differential Biomarkers in the Milk of Holstein Cows with Different Somatic Cells Count Levels. Animals. 13(15). 2446–2446. 6 indexed citations
12.
Wang, Wenjing, et al.. (2023). Integrating Analysis to Identify Differential circRNAs Involved in Goat Endometrial Receptivity. International Journal of Molecular Sciences. 24(2). 1531–1531. 2 indexed citations
13.
Xu, Zheng, et al.. (2021). Analysis of Transcripts of Uncertain Coding Potential Using RNA Sequencing During the Preattachment Phase in Goat Endometrium. DNA and Cell Biology. 40(7). 998–1008. 4 indexed citations
14.
He, Xiaoyan, Cheng Tan, Zicong Li, et al.. (2019). Characterization and comparative analyses of transcriptomes of cloned and in vivo fertilized porcine pre-implantation embryos. Biology Open. 8(4). 7 indexed citations
15.
Wang, Xingwang, Junsong Shi, Gengyuan Cai, et al.. (2019). Overexpression of MBD3 Improves Reprogramming of Cloned Pig Embryos. Cellular Reprogramming. 21(5). 221–228. 6 indexed citations
16.
Yang, Yang, Dan Wu, Dewu Liu, et al.. (2017). Mutation of the XIST gene upregulates expression of X-linked genes but decreases the developmental rates of cloned male porcine embryos. Molecular Reproduction and Development. 84(6). 525–534. 4 indexed citations
17.
Ding, Rongrong, et al.. (2016). Genetic comparison of carcass and meat quality traits of different strain Duroc three-way cross hybrid pigs.. Journal of the South China Agricultural University. 37(6). 46–51. 1 indexed citations
18.
Li, Zicong, Junsong Shi, Dewu Liu, et al.. (2013). Effects of Donor Fibroblast Cell Type and Transferred Cloned Embryo Number on the Efficiency of Pig Cloning. Cellular Reprogramming. 15(1). 35–42. 36 indexed citations
19.
Li, Zicong, Xiaoyan He, Liwen Chen, et al.. (2013). Bone Marrow Mesenchymal Stem Cells Are an Attractive Donor Cell Type for Production of Cloned Pigs As Well As Genetically Modified Cloned Pigs by Somatic Cell Nuclear Transfer. Cellular Reprogramming. 15(5). 459–470. 34 indexed citations
20.
Liu, Dewu. (2010). Changes of Leptin and Leptin Receptor Gene Expression in Subcutaneous Fat and Hypothalamus of Lantang and Landrace Pigs. Huazhong Nongye Daxue xuebao. 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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