Kai Zhao

2.2k total citations · 1 hit paper
73 papers, 876 citations indexed

About

Kai Zhao is a scholar working on Genetics, Aquatic Science and Nature and Landscape Conservation. According to data from OpenAlex, Kai Zhao has authored 73 papers receiving a total of 876 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Genetics, 21 papers in Aquatic Science and 19 papers in Nature and Landscape Conservation. Recurrent topics in Kai Zhao's work include Fish Ecology and Management Studies (16 papers), Fish Biology and Ecology Studies (15 papers) and Genetic diversity and population structure (11 papers). Kai Zhao is often cited by papers focused on Fish Ecology and Management Studies (16 papers), Fish Biology and Ecology Studies (15 papers) and Genetic diversity and population structure (11 papers). Kai Zhao collaborates with scholars based in China, United States and Canada. Kai Zhao's co-authors include Cunfang Zhang, Chao Tong, Fei Tian, Renyi Zhang, Zuogang Peng, Shunan Zhao, Ge Song, Ruiping Liu, Jiaqi Wang and Yongtao Tang and has published in prestigious journals such as Advanced Materials, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Kai Zhao

64 papers receiving 857 citations

Hit Papers

Risk control of antibiotics, antibiotic resistance genes ... 2023 2026 2024 2025 2023 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Risk control of antibiotics, antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB) during sewage sludge treatment and disposal: A review
    2023 119 citations Jiaqi Wang, Kai Zhao et al. The Science of The Total Environment profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kai Zhao China 17 241 214 201 181 168 73 876
Sigurlaug Skírnisdóttir Iceland 15 135 0.6× 361 1.7× 60 0.3× 398 2.2× 97 0.6× 29 753
Giles Goetz United States 19 254 1.1× 269 1.3× 195 1.0× 253 1.4× 197 1.2× 31 1.1k
Ingrid Bakke Norway 28 175 0.7× 613 2.9× 416 2.1× 586 3.2× 96 0.6× 64 1.9k
Maurizio Manera Italy 28 79 0.3× 914 4.3× 494 2.5× 169 0.9× 152 0.9× 92 2.4k
Pengzhi Qi China 19 73 0.3× 156 0.7× 130 0.6× 189 1.0× 34 0.2× 82 1.0k
José Roberto Machado Cunha da Silva Brazil 20 59 0.2× 215 1.0× 278 1.4× 108 0.6× 58 0.3× 84 1.1k
Ahmed Siah Canada 21 42 0.2× 263 1.2× 139 0.7× 176 1.0× 55 0.3× 46 1.0k
Wolfgang K. Vogelbein United States 28 95 0.4× 559 2.6× 192 1.0× 354 2.0× 231 1.4× 79 2.1k
Francesca Carella Italy 20 38 0.2× 522 2.4× 136 0.7× 140 0.8× 64 0.4× 62 1.2k
Miroslava Palíková Czechia 19 40 0.2× 322 1.5× 202 1.0× 56 0.3× 92 0.5× 81 944

Countries citing papers authored by Kai Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Kai Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Kai Zhao. A scholar is included among the top collaborators of Kai Zhao 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 Kai Zhao. Kai Zhao 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.
Li, Xue, Buying Han, Dehui Liu, et al.. (2025). Transcriptomic and flavor metabolomic exploration of the genetic basis of meat quality and flavor in Tibetan sheep. BMC Genomics. 26(1). 867–867.
2.
Sui, Ruifang, Delin Qi, Songzhe Fu, et al.. (2025). Transcriptomics and proteomics provide insights into the adaptative strategies of Tibetan naked carps (Gymnocypris przewalskii) to saline-alkaline variations. BMC Genomics. 26(1). 162–162. 4 indexed citations
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Feng, Yu, Jia Song, Dongsheng Wang, et al.. (2025). Screening and verification of EmMYB5 in flavonoids biosynthesis in Elaeagnus mollis dies kernel. Industrial Crops and Products. 236. 122113–122113.
5.
Zhao, Kai, Xue Li, Dehui Liu, et al.. (2024). Genetic Variations of MSTN and Callipyge in Tibetan Sheep: Implications for Early Growth Traits. Genes. 15(7). 921–921. 4 indexed citations
6.
Liu, Dehui, Xue Li, Jincai Zhao, et al.. (2024). Genome-wide association studies of body size traits in Tibetan sheep. BMC Genomics. 25(1). 739–739. 6 indexed citations
7.
Wang, Jiaqi, et al.. (2023). Risk control of antibiotics, antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB) during sewage sludge treatment and disposal: A review. The Science of The Total Environment. 877. 162772–162772. 119 indexed citations breakdown →
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Li, Xue, Ning Ding, Zhichao Zhang, et al.. (2022). Identification of SSTR5 Gene Polymorphisms and Their Association With Growth Traits in Hulun Buir Sheep. Frontiers in Genetics. 13. 831599–831599. 4 indexed citations
12.
Liu, Sijia, Xiaohuan Li, Delin Qi, et al.. (2022). Genome-wide characterization of the Elovl gene family in Gymnocypris przewalskii and their potential roles in adaptation to cold temperature. Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 262. 110759–110759. 9 indexed citations
13.
Qi, Delin, Sijia Liu, Hongfang Qi, et al.. (2022). Physiological, morphological and transcriptomic responses of Tibetan naked carps (Gymnocypris przewalskii) to salinity variations. Comparative Biochemistry and Physiology Part D Genomics and Proteomics. 42. 100982–100982. 15 indexed citations
14.
Qin, Xiaoli, Depeng Zhang, Xinjun Qiu, et al.. (2022). 2-Hydroxy-4-(Methylthio) Butanoic Acid Isopropyl Ester Supplementation Altered Ruminal and Cecal Bacterial Composition and Improved Growth Performance of Finishing Beef Cattle. Frontiers in Nutrition. 9. 833881–833881. 12 indexed citations
15.
Zhang, Zhichao, et al.. (2022). Comparison and analysis on sheep meat quality and flavor under pasture-based fattening contrast to intensive pasture-based feeding system. Animal Bioscience. 35(7). 1069–1079. 14 indexed citations
16.
Chen, Jing, et al.. (2021). Development of A MERS-CoV Replicon Cell Line for Antiviral Screening. Virologica Sinica. 36(4). 730–735. 6 indexed citations
17.
Zhang, Yu, et al.. (2020). Mitochondrial genome and phylogenetic relationship of Gymnocypris eckloni (Schizothoracinae) in Qaidam river basin. Genomics. 112(6). 4316–4321. 9 indexed citations
18.
Zhao, Yahui, et al.. (2020). Species diversity and conservation of freshwater fishes in the Yellow River basin. Biodiversity Science. 28(12). 1496–1510. 24 indexed citations
19.
Liu, Sijia, et al.. (2020). Comparative transcriptome of reproductive axis in Chinese indigenous sheep with different FecB genotypes and prolificacies. Animal Reproduction Science. 223. 106624–106624. 11 indexed citations
20.

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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