Zhiping Cao

954 total citations
54 papers, 640 citations indexed

About

Zhiping Cao is a scholar working on Genetics, Plant Science and Molecular Biology. According to data from OpenAlex, Zhiping Cao has authored 54 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 15 papers in Plant Science and 10 papers in Molecular Biology. Recurrent topics in Zhiping Cao's work include Genetic and phenotypic traits in livestock (13 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Animal Nutrition and Physiology (9 papers). Zhiping Cao is often cited by papers focused on Genetic and phenotypic traits in livestock (13 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and Animal Nutrition and Physiology (9 papers). Zhiping Cao collaborates with scholars based in China, Czechia and United States. Zhiping Cao's co-authors include Zdeněk P. Bažant, Cheng Hu, Hui Li, Yumao Li, Peng Luan, Hui Zhang, Yosef Steinberger, Jing Wu, Yuying Hu and Dianpeng Zhang and has published in prestigious journals such as Nature Communications, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Zhiping Cao

52 papers receiving 597 citations

Peers

Zhiping Cao

GENET

CSE

Mary E Drewnoski United States

Minxia Zhang China

J. Chen China

Carlos Eduardo Delfino Vieira Brazil

C. Wang China

Magda Aparecida de Lima Brazil

Jemaneh Habtewold Canada

Katsumi Ohyama Japan

Mary E Drewnoski United States

Zhiping Cao

16 ×0.1

187 ×1.3

GENET

16 ×0.1

CSE

83 ×0.7

91 ×0.8

Citations per year, relative to Zhiping Cao Zhiping Cao (= 1×) peers Mary E Drewnoski

Countries citing papers authored by Zhiping Cao

Since Specialization

Citations

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

Fields of papers citing papers by Zhiping Cao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhiping Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhiping Cao. A scholar is included among the top collaborators of Zhiping Cao 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 Zhiping Cao. Zhiping Cao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Chen, Hongsheng, Xintong Liu, Cheng Chang, et al.. (2025). Optimization of Genomic Breeding Value Estimation Model for Abdominal Fat Traits Based on Machine Learning. Animals. 15(19). 2843–2843.

Zhang, Huili, Xiaoxiang Cao, Li Leng, et al.. (2025). Functional analysis of lncRNAs in lipid metabolism of fat and lean line broiler embryonic livers. Poultry Science. 104(8). 105261–105261.

Chen, Hongsheng, Cheng Chang, Fuyang Zhang, et al.. (2025). Identification and Pathway Analysis of SNP Loci Affecting Abdominal Fat Deposition in Broilers. Animals. 15(19). 2811–2811. 1 indexed citations

Wang, Shuping, Yan Song, Zhiping Cao, et al.. (2024). CTGF Inhibits the Differentiation of Chicken Preadipocytes via the TGFβ/Smad3 Signaling Pathway or by Inducing the Expression of ACTG2. Journal of Agricultural and Food Chemistry. 72(35). 19413–19423. 1 indexed citations

Bai, Xue, Cheng Chang, Xinquan Li, et al.. (2024). Integrative 3D genomics with multi-omics analysis and functional validation of genetic regulatory mechanisms of abdominal fat deposition in chickens. Nature Communications. 15(1). 9274–9274. 9 indexed citations

Chen, Hongyan, Qi Zhang, Li Leng, et al.. (2023). HBP1 promotes chicken preadipocyte proliferation via directly repressing SOCS3 transcription. International Journal of Biological Macromolecules. 256(Pt 2). 128414–128414. 3 indexed citations

Ma, Yanyan, Jing Yang, Li Leng, et al.. (2023). Comparative analyses of laying performance and follicular development characteristics between fat and lean broiler lines. Poultry Science. 103(1). 103250–103250. 7 indexed citations

Zhang, Xinyang, Chang Liu, Zhiping Cao, et al.. (2021). Transcription Factor 21 Promotes Chicken Adipocyte Differentiation at Least in Part via Activating MAPK/JNK Signaling. Genes. 12(12). 1971–1971. 6 indexed citations

Zhang, Xinyang, Yanyan Ma, Ning Wang, et al.. (2021). Genome-wide survey and functional analysis reveal TCF21 promotes chicken preadipocyte differentiation by directly upregulating HTR2A. Biochemical and Biophysical Research Communications. 587. 131–138. 5 indexed citations

10.

Zhang, Hui, Luke Kramer, Xinyang Zhang, et al.. (2020). Haplotype-based genome-wide association studies for carcass and growth traits in chicken. Poultry Science. 99(5). 2349–2361. 44 indexed citations

11.

Li, Rui, Yumao Li, Zhiping Cao, et al.. (2020). RXRα Positively Regulates Expression of the Chicken PLIN1 Gene in a PPARγ-Independent Manner and Promotes Adipogenesis. Frontiers in Cell and Developmental Biology. 8. 349–349. 12 indexed citations

12.

Zhang, Xinyang, Chang Liu, Zhi‐Qiang Du, et al.. (2019). A Novel Regulator of Preadipocyte Differentiation, Transcription Factor TCF21, Functions Partially Through Promoting LPL Expression. Frontiers in Physiology. 10. 458–458. 16 indexed citations

13.

Wei, Na, Xinyang Zhang, Lili Yang, et al.. (2018). Important candidate genes for abdominal fat content identified by linkage disequilibrium and fixation index information. Poultry Science. 98(2). 581–589. 10 indexed citations

14.

Zhang, Qi, Songsong Xu, Peng Luan, et al.. (2015). Differential expression of six chicken genes associated with fatness traits in a divergently selected broiler population. Molecular and Cellular Probes. 30(1). 1–5. 12 indexed citations

15.

Xu, Songsong, Hui Zhang, Yumao Li, et al.. (2015). Differential expression of six genes and correlation with fatness traits in a unique broiler population. Saudi Journal of Biological Sciences. 24(4). 945–949. 22 indexed citations

16.

Wang, Weishi, Zhi‐Qiang Du, Yuxiang Wang, et al.. (2015). Expression Profiling of Preadipocyte MicroRNAs by Deep Sequencing on Chicken Lines Divergently Selected for Abdominal Fatness. PLoS ONE. 10(2). e0117843–e0117843. 24 indexed citations

17.

Wu, Jing, et al.. (2013). [Fluorescence properties of municipal wastewater with industrial wastewater as major components].. PubMed. 33(2). 414–7. 1 indexed citations

18.

Wu, Jing, et al.. (2012). [Fluorescence fingerprint properties of refinery wastewater].. PubMed. 32(2). 415–9. 1 indexed citations

19.

Chen, Yunfeng, et al.. (2008). Effects of different soil management practices on soil free-living nematode community structure, Eastern China. Canadian Journal of Soil Science. 88(1). 115–127. 19 indexed citations

20.

Dong, Ming, et al.. (2005). Responses of Caryopsis Germination, Seedling Emergence, and Development to Sand Water Content of Agropyron cristatum (L.) Gaertn. and Bromus inermis Leyss. Journal of Integrative Plant Biology. 47(12). 1450–1458. 5 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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