Kehua Wang

1.1k total citations
61 papers, 761 citations indexed

About

Kehua Wang is a scholar working on Genetics, Animal Science and Zoology and Molecular Biology. According to data from OpenAlex, Kehua Wang has authored 61 papers receiving a total of 761 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Genetics, 31 papers in Animal Science and Zoology and 16 papers in Molecular Biology. Recurrent topics in Kehua Wang's work include Animal Nutrition and Physiology (26 papers), Genetic and phenotypic traits in livestock (23 papers) and Genetic Mapping and Diversity in Plants and Animals (18 papers). Kehua Wang is often cited by papers focused on Animal Nutrition and Physiology (26 papers), Genetic and phenotypic traits in livestock (23 papers) and Genetic Mapping and Diversity in Plants and Animals (18 papers). Kehua Wang collaborates with scholars based in China, United States and France. Kehua Wang's co-authors include Ning Yang, Taocun Dou, Manman Shen, Liang Qu, Congjiao Sun, Meng Ma, Jingwei Yuan, Lujiang Qu, Guoqiang Yi and Jun Guo and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Scientific Reports.

In The Last Decade

Kehua Wang

57 papers receiving 738 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kehua Wang China	16	485	389	198	85	61	61	761
Shouzhi Wang China	14	324 0.7×	194 0.5×	226 1.1×	117 1.4×	57 0.9×	39	625
Mervi Honkatukia Finland	12	350 0.7×	237 0.6×	103 0.5×	63 0.7×	60 1.0×	27	543
Kacper Żukowski Poland	14	408 0.8×	157 0.4×	240 1.2×	164 1.9×	53 0.9×	54	660
Hyun‐Tae Lim South Korea	15	364 0.8×	302 0.8×	164 0.8×	106 1.2×	29 0.5×	62	643
Yanzhang Gong China	16	300 0.6×	141 0.4×	228 1.2×	119 1.4×	33 0.5×	58	659
H. van der Steen Australia	4	395 0.8×	123 0.3×	110 0.6×	48 0.6×	64 1.0×	6	521
Katarzyna Piórkowska Poland	17	484 1.0×	331 0.9×	354 1.8×	185 2.2×	22 0.4×	100	951
Huirong Mao China	15	304 0.6×	105 0.3×	154 0.8×	122 1.4×	44 0.7×	33	510
Sung-Soo Lee South Korea	15	262 0.5×	102 0.3×	174 0.9×	55 0.6×	33 0.5×	67	507

Countries citing papers authored by Kehua Wang

Since Specialization

Citations

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

Fields of papers citing papers by Kehua Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kehua Wang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Li, Shengping, Kai Wang, Hongzhi Wang, et al.. (2024). Distribution and environmental dissemination of antibiotic resistance genes in poultry farms and surrounding ecosystems. Poultry Science. 104(1). 104665–104665. 5 indexed citations

Zhu, Zheng, et al.. (2023). A non-local grouping tensor train decomposition model for travel demand analysis concerning categorical independent variables. Transportation Research Part C Emerging Technologies. 157. 104396–104396. 2 indexed citations

Shen, Manman, Jian Lü, Kehua Wang, et al.. (2022). Effects of Supplementation of Moringa Oleifera Leaf Powder on Some Reproductive Performance in Laying Hens. Brazilian Journal of Poultry Science. 24(2). 1 indexed citations

Nie, Changsheng, Liang Qu, Xinghua Li, et al.. (2021). Genomic Regions Related to White/Black Tail Feather Color in Dwarf Chickens Identified Using a Genome-Wide Association Study. Frontiers in Genetics. 12. 566047–566047. 9 indexed citations

Xue, Qian, Yuxia Cao, Chenghao Zhou, et al.. (2020). Identification of genes involved in inbreeding depression of reproduction in Langshan chickens. Animal Bioscience. 34(6). 975–984. 8 indexed citations

Han, Wei, et al.. (2020). Genome-wide analysis of the role of DNA methylation in inbreeding depression of reproduction in Langshan chicken. Genomics. 112(4). 2677–2687. 19 indexed citations

Guo, Jun, et al.. (2019). Genetic evaluation of eggshell color based on additive and dominance models in laying hens. Asian-Australasian Journal of Animal Sciences. 33(8). 1217–1223. 6 indexed citations

Ma, Meng, et al.. (2018). Genome-wide association of spleen weight in layer chicken.. Zhongguo nongye Kexue. 51(6). 1213–1222. 1 indexed citations

Zhang, Yani, Yingjie Wang, Qisheng Zuo, et al.. (2016). Effects of the Transforming Growth Factor Beta Signaling Pathway on the Differentiation of Chicken Embryonic Stem Cells into Male Germ Cells. Cellular Reprogramming. 18(6). 401–410. 22 indexed citations

10.

Jun, Guo, et al.. (2016). Direct and maternal genetic effects for traits at the first egg in Rugao yellow chickens.. Journal of the South China Agricultural University. 37(2). 1–6. 1 indexed citations

11.

Sun, Congjiao, Guoqiang Yi, Jingwei Yuan, et al.. (2015). Genome-wide association study revealed a promising region and candidate genes for eggshell quality in an F2 resource population. BMC Genomics. 16(1). 565–565. 37 indexed citations

12.

Yuan, Jingwei, Taocun Dou, Meng Ma, et al.. (2015). Genetic parameters of feed efficiency traits in laying period of chickens. Poultry Science. 94(7). 1470–1475. 37 indexed citations

13.

Wang, Kehua, et al.. (2015). Genome-wide polymorphisms between the parents of an elite hybrid rice and the development of a novel set of PCR-based InDel markers. Genetics and Molecular Research. 14(2). 3209–3222. 3 indexed citations

14.

Han, Wei, Kehua Wang, Yijun Su, et al.. (2015). High-Throughput Sequencing Reveals Hypothalamic MicroRNAs as Novel Partners Involved in Timing the Rapid Development of Chicken (Gallus gallus) Gonads. PLoS ONE. 10(6). e0129738–e0129738. 15 indexed citations

15.

Wang, Kehua, et al.. (2012). Comparison and analysis for egg quality of seven layer breeds.. 34(5). 23–31. 1 indexed citations

16.

Wang, Kehua, et al.. (2010). Comparison of some immune traits among different chicken breeds.. Zhongguo shouyi xuebao. 30(3). 317–322. 1 indexed citations

17.

Gao, Yushi, et al.. (2009). The study on DNA barcodes of CO I gene in Langshan and Luyuan chichen breeds.. Journal of Yangzhou University. 30(4). 26–29.

18.

Tu, Yunjie, et al.. (2009). H-FABP gene expression with meat quality in different chicken breeds.. Journal of Yangzhou University. 30(4). 23–29. 1 indexed citations

19.

Tu, Yunjie, et al.. (2007). The genetic diversity analysis of mtDNA COI genes in six indigenous chicken breeds in China. Journal of Yangzhou University. 28(3). 31–33. 1 indexed citations

20.

Wang, Jinyu, et al.. (2004). Study on the Correlation between OPAY02 Marker and Early Performance in Xiaoshan and Its Hybrid Offspring. 25(1). 5–9. 1 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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