Jin-Ping Hao

1.0k total citations · 1 hit paper
25 papers, 642 citations indexed

About

Jin-Ping Hao is a scholar working on Genetics, Animal Science and Zoology and Molecular Biology. According to data from OpenAlex, Jin-Ping Hao has authored 25 papers receiving a total of 642 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Genetics, 11 papers in Animal Science and Zoology and 5 papers in Molecular Biology. Recurrent topics in Jin-Ping Hao's work include Genetic and phenotypic traits in livestock (14 papers), Genetic Mapping and Diversity in Plants and Animals (8 papers) and Animal Nutrition and Physiology (7 papers). Jin-Ping Hao is often cited by papers focused on Genetic and phenotypic traits in livestock (14 papers), Genetic Mapping and Diversity in Plants and Animals (8 papers) and Animal Nutrition and Physiology (7 papers). Jin-Ping Hao collaborates with scholars based in China, United Kingdom and Czechia. Jin-Ping Hao's co-authors include Zhuocheng Hou, Fang‐Xi Yang, Feng Zhu, Yuze Yang, Si-Rui Chen, Shengqiang Hu, Chris Haley, Changxin Wu, Yinhua Huang and Xiaoning Wu and has published in prestigious journals such as Genetics, European Journal of Pharmacology and BMC Genomics.

In The Last Decade

Jin-Ping Hao

23 papers receiving 629 citations

Hit Papers

Genome-wide association study reveals novel loci associat... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jin-Ping Hao China 12 230 215 137 136 85 25 642
Daoqing Gong China 18 192 0.8× 471 2.2× 88 0.6× 247 1.8× 152 1.8× 82 981
Shuisheng Hou China 16 100 0.4× 214 1.0× 38 0.3× 274 2.0× 45 0.5× 70 590
Donghyun Shin South Korea 16 315 1.4× 349 1.6× 86 0.6× 165 1.2× 135 1.6× 79 844
Yanhong Chen China 13 237 1.0× 230 1.1× 112 0.8× 165 1.2× 106 1.2× 43 683
M. Szydłowski Poland 18 563 2.4× 229 1.1× 137 1.0× 269 2.0× 118 1.4× 72 923
Zhen Tan China 18 235 1.0× 384 1.8× 180 1.3× 206 1.5× 178 2.1× 54 936
T. Mitsuhashi Japan 17 359 1.6× 264 1.2× 61 0.4× 454 3.3× 62 0.7× 37 1.1k
Guiqin Wu China 15 284 1.2× 282 1.3× 69 0.5× 327 2.4× 32 0.4× 42 754
Simrinder Singh Sodhi India 18 105 0.5× 241 1.1× 137 1.0× 168 1.2× 96 1.1× 58 833
Yongqing Zeng China 15 159 0.7× 259 1.2× 34 0.2× 142 1.0× 164 1.9× 66 646

Countries citing papers authored by Jin-Ping Hao

Since Specialization
Citations

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

Fields of papers citing papers by Jin-Ping Hao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jin-Ping Hao. 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 Jin-Ping Hao. The network helps show where Jin-Ping Hao may publish in the future.

Co-authorship network of co-authors of Jin-Ping Hao

This figure shows the co-authorship network connecting the top 25 collaborators of Jin-Ping Hao. A scholar is included among the top collaborators of Jin-Ping Hao 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 Jin-Ping Hao. Jin-Ping Hao 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
2.
Zhou, Jun, Jiang‐Zhou Yu, Fang‐Xi Yang, et al.. (2024). Optimizing Breeding Strategies for Pekin Ducks Using Genomic Selection: Genetic Parameter Evaluation and Selection Progress Analysis in Reproductive Traits. Applied Sciences. 15(1). 194–194. 3 indexed citations
3.
Gao, Dan, Jin-Ping Hao, Boya Li, et al.. (2023). Tetrahydroxy stilbene glycoside ameliorates neuroinflammation for Alzheimer's disease via cGAS-STING. European Journal of Pharmacology. 953. 175809–175809. 42 indexed citations
4.
Zhang, Jin, Kaihui Liu, Ying Zhang, et al.. (2023). Application of transcriptome in time analysis and donor characterization in blood samples.. PubMed. 45(1). 52–66.
5.
Zhu, Feng, et al.. (2021). Genome-wide association study reveals novel loci associated with feeding behavior in Pekin ducks. BMC Genomics. 22(1). 334–334. 4 indexed citations
6.
Zhang, Fan, Feng Zhu, Fang‐Xi Yang, Jin-Ping Hao, & Zhuocheng Hou. (2021). Genomic selection for meat quality traits in Pekin duck. Animal Genetics. 53(1). 94–100. 14 indexed citations
7.
Liu, Weiwei, Fan Zhang, Feng Zhu, et al.. (2020). Genome-wide association study of bone quality and feed efficiency-related traits in Pekin ducks. Genomics. 112(6). 5021–5028. 10 indexed citations
8.
Zhang, Qian, et al.. (2020). LncRNA PVT1 exacerbates the inflammation and cell‐barrier injury during asthma by regulating miR‐149. Journal of Biochemical and Molecular Toxicology. 34(11). e22563–e22563. 31 indexed citations
9.
Zhu, Feng, et al.. (2020). Selection response and genetic parameter estimation of feeding behavior traits in Pekin ducks. Poultry Science. 99(5). 2375–2384. 14 indexed citations
10.
Zhu, Feng, et al.. (2019). Genome-wide association study of the level of blood components in Pekin ducks. Genomics. 112(1). 379–387. 14 indexed citations
11.
Chen, Si-Rui, et al.. (2019). Comparison of carcass and meat quality traits between lean and fat Pekin ducks. Animal Bioscience. 34(7). 1193–1201. 25 indexed citations
12.
Zhu, Feng, Yuze Yang, Fang‐Xi Yang, et al.. (2019). Genome-wide association study reveals novel loci associated with body size and carcass yields in Pekin ducks. BMC Genomics. 20(1). 1–1. 251 indexed citations breakdown →
13.
Zhu, Feng, et al.. (2019). Genome-Wide Association Study of Growth and Feeding Traits in Pekin Ducks. Frontiers in Genetics. 10. 702–702. 22 indexed citations
14.
Wang, Le, et al.. (2018). A 21-plex system of STRs integrated with Y-STR DYS391 and ABO typing for forensic DNA analysis. Australian Journal of Forensic Sciences. 52(1). 16–26. 1 indexed citations
15.
Zhu, Feng, et al.. (2018). In vivo prediction of the carcass fatness using live body measurements in Pekin ducks. Poultry Science. 97(7). 2365–2371. 25 indexed citations
16.
Zhu, Feng, et al.. (2017). Systematic analysis of feeding behaviors and their effects on feed efficiency in Pekin ducks. Journal of Animal Science and Biotechnology. 8(1). 81–81. 10 indexed citations
17.
Wu, Fei, et al.. (2009). Evaluation of genetic diversity and relationships within and between two breeds of duck based on microsatellite markers. Progress in Natural Science Materials International. 19(11). 1581–1586. 9 indexed citations
18.
Huang, Yinhua, Chris Haley, Shengqiang Hu, et al.. (2007). Genetic mapping of quantitative trait loci affecting carcass and meat quality traits in Beijing ducks (Anas platyrhynchos). Animal Genetics. 38(2). 114–119. 24 indexed citations
19.
Huang, Yinhua, Chris Haley, Shengqiang Hu, et al.. (2007). Detection of quantitative trait loci for body weights and conformation traits in Beijing ducks. Animal Genetics. 38(5). 525–526. 7 indexed citations
20.
Hao, Jin-Ping, et al.. (1989). Regulation of extracellular proteins and α-amylase secretion by temperature inBacillus subtilis. Folia Microbiologica. 34(3). 179–184. 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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