Renhai Peng

1.6k total citations
69 papers, 824 citations indexed

About

Renhai Peng is a scholar working on Plant Science, Molecular Biology and Endocrinology. According to data from OpenAlex, Renhai Peng has authored 69 papers receiving a total of 824 indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Plant Science, 23 papers in Molecular Biology and 10 papers in Endocrinology. Recurrent topics in Renhai Peng's work include Research in Cotton Cultivation (48 papers), Plant Virus Research Studies (34 papers) and Chromosomal and Genetic Variations (11 papers). Renhai Peng is often cited by papers focused on Research in Cotton Cultivation (48 papers), Plant Virus Research Studies (34 papers) and Chromosomal and Genetic Variations (11 papers). Renhai Peng collaborates with scholars based in China, United States and Kenya. Renhai Peng's co-authors include Baohong Zhang, Fang Liu, Kunbo Wang, Xiaoyan Cai, Zhongli Zhou, Richard Odongo Magwanga, Joy Nyangasi Kirungu, Xingxing Wang, Yuqing Hou and Yangyang Wei and has published in prestigious journals such as Nature Genetics, PLoS ONE and Scientific Reports.

In The Last Decade

Renhai Peng

64 papers receiving 816 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Renhai Peng China 17 687 344 65 34 32 69 824
Yuanyuan Jiang China 15 523 0.8× 345 1.0× 28 0.4× 15 0.4× 24 0.8× 53 732
Ran Hovav Israel 21 1.1k 1.6× 403 1.2× 70 1.1× 56 1.6× 11 0.3× 43 1.2k
Yǒulù Yuán China 17 893 1.3× 226 0.7× 54 0.8× 107 3.1× 19 0.6× 58 1.1k
Zupeng Wang China 13 368 0.5× 425 1.2× 22 0.3× 24 0.7× 28 0.9× 27 647
Shizhou Yu China 16 602 0.9× 231 0.7× 191 2.9× 54 1.6× 21 0.7× 42 742
Bingliang Liu China 14 503 0.7× 225 0.7× 25 0.4× 37 1.1× 9 0.3× 42 612
Raúl Castanera Spain 16 658 1.0× 325 0.9× 65 1.0× 20 0.6× 80 2.5× 32 820
Geng‐Qing Huang China 17 824 1.2× 528 1.5× 17 0.3× 26 0.8× 34 1.1× 28 895
Zhaoe Pan China 20 991 1.4× 344 1.0× 78 1.2× 110 3.2× 13 0.4× 70 1.1k

Countries citing papers authored by Renhai Peng

Since Specialization
Citations

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

Fields of papers citing papers by Renhai Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Renhai Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Renhai Peng. A scholar is included among the top collaborators of Renhai Peng 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 Renhai Peng. Renhai Peng 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.
Hu, Nan, Yanhua Li, Li Xu, et al.. (2025). pHNRhCas9NG, single expression cassette-based dual-component dual-transcription unit CRISPR/Cas9 system for plant genome editing. Trends in biotechnology. 43(7). 1788–1808. 1 indexed citations
2.
Xu, Zhongping, Guanying Wang, Ruipeng Wang, et al.. (2025). Genome assembly of two allotetraploid cotton germplasms reveals mechanisms of somatic embryogenesis and enables precise genome editing. Nature Genetics. 57(8). 2028–2039.
3.
4.
Wang, Nian, Qingying Meng, Zhiyong Xu, et al.. (2025). Gossypium latifolium genome reveals the genetic basis of domestication of upland cotton from semi-wild races to cultivars. The Crop Journal. 13(3). 929–941. 2 indexed citations
5.
Zhai, Jingjing, Shu Geng, Shaoliang Zhang, et al.. (2025). Genome-wide identification and functional analysis of TCX gene family and the critical role of GhTCX17 in response to drought and salt stress in cotton. Functional & Integrative Genomics. 25(1). 129–129. 1 indexed citations
6.
Wang, Tao, Sumei Wan, Yan Tong, et al.. (2024). Genome-wide identification and functional analysis of the SiCIN gene family in foxtail millet (Setaria italica L.). Gene. 921. 148499–148499. 3 indexed citations
7.
Wang, Xiaoyan, Chaojun Zhang, Nuohan Wang, et al.. (2024). GhFPF1 positively regulates shade avoidance responses via interacting with GhNF-YA3 in cotton. Industrial Crops and Products. 223. 120193–120193. 1 indexed citations
8.
Li, Pengtao, Zhihao Sun, Yu Chen, et al.. (2024). Integrated Transcriptomic and Metabolomic Analysis of G. hirsutum and G. barbadense Responses to Verticillium Wilt Infection. International Journal of Molecular Sciences. 26(1). 28–28. 1 indexed citations
9.
Peng, Renhai, et al.. (2024). Single-cell RNA sequencing opens a new era for cotton genomic research and gene functional analysis. Journal of Cotton Research. 7(1). 12 indexed citations
10.
Wei, Yangyang, Sumei Wan, Yi Li, et al.. (2023). Flow cytometry-based cell cycle synchronization and transcriptome analysis in cotton (Gossypium arboretum L.). Industrial Crops and Products. 201. 116889–116889. 2 indexed citations
11.
Wei, Yangyang, Pengtao Li, Quánwěi Lú, et al.. (2023). Genome-Wide Identification and Functional Analysis of RF2 Gene Family and the Critical Role of GhRF2-32 in Response to Drought Stress in Cotton. Plants. 12(14). 2613–2613. 6 indexed citations
12.
Xiāo, Xiànghuī, Ruixian Liu, Jǔwǔ Gōng, et al.. (2023). Fine mapping and candidate gene analysis of qFL-A12-5: a fiber length-related QTL introgressed from Gossypium barbadense into Gossypium hirsutum. Theoretical and Applied Genetics. 136(3). 48–48. 7 indexed citations
13.
14.
Li, Ziyin, Yùzhēn Shí, Xiànghuī Xiāo, et al.. (2023). Genome-wide characterization of trichome birefringence-like genes provides insights into fiber yield improvement. Frontiers in Plant Science. 14. 1127760–1127760. 11 indexed citations
15.
Li, Pengtao, Shuang Cheng, Yuling Liu, et al.. (2022). Protoplast Dissociation and Transcriptome Analysis Provides Insights to Salt Stress Response in Cotton. International Journal of Molecular Sciences. 23(5). 2845–2845. 18 indexed citations
16.
Magwanga, Richard Odongo, Xiaoyan Cai, Joy Nyangasi Kirungu, et al.. (2021). Functional Characterization of GhACX3 Gene Reveals Its Significant Role in Enhancing Drought and Salt Stress Tolerance in Cotton. Frontiers in Plant Science. 12. 658755–658755. 24 indexed citations
17.
Peng, Renhai, Don C. Jones, Fang Liu, & Baohong Zhang. (2020). From Sequencing to Genome Editing for Cotton Improvement. Trends in biotechnology. 39(3). 221–224. 36 indexed citations
18.
Liu, Yuling, et al.. (2020). Cloning and preliminary verification of telomere-associated sequences in upland cotton. ZooKeys. 14(2). 183–195. 1 indexed citations
19.
Liu, Yuling, Zhen Liu, Zhaoguo Li, et al.. (2017). Construction and Primary Application of Oligos Fluorescence in situ Hybridization Technology in Cotton. Mianhua xuebao. 29(3). 213–221.
20.
Liu, Yuling, Renhai Peng, Fang Liu, et al.. (2016). A Gossypium BAC clone contains key repeat components distinguishing sub-genome of allotetraploidy cottons. Molecular Cytogenetics. 9(1). 27–27. 6 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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