Shuli Liu

2.1k total citations
36 papers, 685 citations indexed

About

Shuli Liu is a scholar working on Genetics, Molecular Biology and Cancer Research. According to data from OpenAlex, Shuli Liu has authored 36 papers receiving a total of 685 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Genetics, 21 papers in Molecular Biology and 9 papers in Cancer Research. Recurrent topics in Shuli Liu's work include Genetic and phenotypic traits in livestock (12 papers), Epigenetics and DNA Methylation (10 papers) and Cancer-related molecular mechanisms research (9 papers). Shuli Liu is often cited by papers focused on Genetic and phenotypic traits in livestock (12 papers), Epigenetics and DNA Methylation (10 papers) and Cancer-related molecular mechanisms research (9 papers). Shuli Liu collaborates with scholars based in China, United States and United Kingdom. Shuli Liu's co-authors include George E. Liu, Lingzhao Fang, Li Ma, Shengli Zhang, Congjun Li, John B. Cole, Ying Yu, Hongwei Yin, Wentao Cai and Keiji Endo and has published in prestigious journals such as The FASEB Journal, Journal of Animal Science and BMC Genomics.

In The Last Decade

Shuli Liu

33 papers receiving 677 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shuli Liu China 15 398 375 172 101 73 36 685
Binyun Cao China 19 393 1.0× 414 1.1× 277 1.6× 48 0.5× 169 2.3× 58 871
Bohui Yang China 18 244 0.6× 399 1.1× 237 1.4× 82 0.8× 74 1.0× 50 716
Pâmela A. Alexandre Australia 16 263 0.7× 482 1.3× 187 1.1× 88 0.9× 152 2.1× 61 785
Kuiqing Cui China 14 368 0.9× 213 0.6× 73 0.4× 21 0.2× 81 1.1× 54 651
Changzhi Zhao China 13 424 1.1× 168 0.4× 64 0.4× 50 0.5× 25 0.3× 32 579
Ralf Bortfeldt Germany 15 152 0.4× 222 0.6× 71 0.4× 65 0.6× 111 1.5× 32 546
Genki Ishihara Japan 12 420 1.1× 253 0.7× 50 0.3× 147 1.5× 18 0.2× 31 747
Christine Große‐Brinkhaus Germany 18 236 0.6× 302 0.8× 120 0.7× 53 0.5× 110 1.5× 51 732
Yiren Gu China 11 514 1.3× 158 0.4× 443 2.6× 65 0.6× 22 0.3× 40 791

Countries citing papers authored by Shuli Liu

Since Specialization
Citations

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

Fields of papers citing papers by Shuli Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuli Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Shuli Liu. A scholar is included among the top collaborators of Shuli 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 Shuli Liu. Shuli 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.
Wu, Xiaoyang, Xibao Wang, Yongquan Shang, et al.. (2025). Identification and Pathogenicity Analysis of Huaxiibacter chinensis Qf-1 in Mink (Neogale vison). Microorganisms. 13(7). 1604–1604. 1 indexed citations
2.
3.
Li, Wenlong, Siyuan Mi, Xueqin Liu, et al.. (2023). Integrating sperm cell transcriptome and seminal plasma metabolome to analyze the molecular regulatory mechanism of sperm motility in Holstein stud bulls. Journal of Animal Science. 101. 6 indexed citations
4.
5.
Yang, Wenjing, Jian Yu, Yuelin Yao, et al.. (2022). Comparative immune-relevant transcriptome reveals the evolutionary basis of complex traits. iScience. 25(12). 105572–105572. 1 indexed citations
6.
Liu, Shuli, Yifan Jiang, Wenlong Li, et al.. (2022). Comparative epigenomics reveals the impact of ruminant-specific regulatory elements on complex traits. BMC Biology. 20(1). 273–273. 14 indexed citations
7.
Zhao, Bingru, Hanpeng Luo, Xixia Huang, et al.. (2021). Comprehensive transcriptome and methylome analysis delineates the biological basis of hair follicle development and wool-related traits in Merino sheep. BMC Biology. 19(1). 197–197. 47 indexed citations
8.
Yang, Jie, Yu Zhang, Shuli Liu, et al.. (2021). Integrative analysis of genome‐wide DNA methylation and gene expression profiles reveals important epigenetic genes related to milk production traits in dairy cattle. Journal of Animal Breeding and Genetics. 138(5). 562–573. 14 indexed citations
9.
Li, Cong, Wentao Cai, Shuli Liu, et al.. (2020). Association of UDP-galactose-4-epimerase with milk protein concentration in the Chinese Holstein population. Asian-Australasian Journal of Animal Sciences. 33(11). 1725–1731. 2 indexed citations
10.
Kang, Xiaolong, Mingxun Li, Mei Liu, et al.. (2020). Copy number variation analysis reveals variants associated with milk production traits in dairy goats. Genomics. 112(6). 4934–4937. 14 indexed citations
11.
Zhou, Yang, Shuli Liu, Yan Hu, et al.. (2020). Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns. BMC Biology. 18(1). 85–85. 38 indexed citations
12.
Fang, Lingzhao, Shuli Liu, Xiaolong Kang, et al.. (2019). Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations. BMC Biology. 17(1). 68–68. 49 indexed citations
13.
Liu, Mei, Lingzhao Fang, Shuli Liu, et al.. (2019). Array CGH-based detection of CNV regions and their potential association with reproduction and other economic traits in Holsteins. BMC Genomics. 20(1). 181–181. 26 indexed citations
14.
Liu, Shuli, Xiaolong Kang, Claudia Rita Catacchio, et al.. (2019). Computational detection and experimental validation of segmental duplications and associated copy number variations in water buffalo ( Bubalus bubalis ). Functional & Integrative Genomics. 19(3). 409–419. 10 indexed citations
15.
Li, Cong, Miao Wang, Wentao Cai, et al.. (2019). Genetic Analyses Confirm SNPs in HSPA8 and ERBB2 are Associated with Milk Protein Concentration in Chinese Holstein Cattle. Genes. 10(2). 104–104. 4 indexed citations
16.
Khan, Muhammad Zahoor, Di Wang, Lei Liu, et al.. (2019). Significant genetic effects of JAK2 and DGAT1 mutations on milk fat content and mastitis resistance in Holsteins. Journal of Dairy Research. 86(4). 388–393. 21 indexed citations
17.
Zhou, Chenghao, Dan Shen, Cong Li, et al.. (2019). Comparative Transcriptomic and Proteomic Analyses Identify Key Genes Associated With Milk Fat Traits in Chinese Holstein Cows. Frontiers in Genetics. 10. 672–672. 16 indexed citations
18.
Liu, Lei, Ning Yang, Guiyun Xu, et al.. (2018). Transgenerational transmission of maternal stimulatory experience in domesticated birds. The FASEB Journal. 32(12). 7002–7017. 11 indexed citations
19.
Liu, Shuli, Shengli Zhang, & Yingyan Yu. (2016). Research progress of regulatory mechanism of DNA methylation in complex traits using monozygotic twins.. PubMed. 38(12). 1043–1055. 1 indexed citations
20.
Morimoto, Takuya, Ryosuke Kadoya, Keiji Endo, et al.. (2008). Enhanced Recombinant Protein Productivity by Genome Reduction in Bacillus subtilis. DNA Research. 15(2). 73–81. 157 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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