Chunbo Miao

1.2k total citations · 1 hit paper
16 papers, 879 citations indexed

About

Chunbo Miao is a scholar working on Molecular Biology, Plant Science and Cell Biology. According to data from OpenAlex, Chunbo Miao has authored 16 papers receiving a total of 879 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Plant Science and 2 papers in Cell Biology. Recurrent topics in Chunbo Miao's work include Plant Molecular Biology Research (6 papers), DNA Repair Mechanisms (5 papers) and Machine Learning in Bioinformatics (3 papers). Chunbo Miao is often cited by papers focused on Plant Molecular Biology Research (6 papers), DNA Repair Mechanisms (5 papers) and Machine Learning in Bioinformatics (3 papers). Chunbo Miao collaborates with scholars based in China, United States and Australia. Chunbo Miao's co-authors include Jian‐Kang Zhu, Kai Hua, Ding Tang, Zhukuan Cheng, Yang Zhao, Lihong Xiao, Changsong Zou, Ray A. Bressan, Mo Wang and Yi Shen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Plant Cell.

In The Last Decade

Chunbo Miao

16 papers receiving 871 citations

Hit Papers

1 papers align trajectories

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.

Mutations in a subfamily of abscisic acid receptor genes promote rice growth and productivity

2018 250 citations Chunbo Miao, Lihong Xiao et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Chunbo Miao China	11	700	551	111	78	27	16	879
Baoxiang Qin China	14	702 1.0×	578 1.0×	117 1.1×	87 1.1×	31 1.1×	34	883
Ushio Fujikura Japan	13	989 1.4×	813 1.5×	74 0.7×	28 0.4×	37 1.4×	17	1.1k
Qiong Luo China	17	579 0.8×	511 0.9×	104 0.9×	83 1.1×	39 1.4×	40	726
Guijie Du China	16	432 0.6×	456 0.8×	68 0.6×	62 0.8×	34 1.3×	27	616
Amy L. Klocko United States	14	413 0.6×	449 0.8×	29 0.3×	51 0.7×	33 1.2×	24	569
Juqiang Yan United States	11	880 1.3×	608 1.1×	150 1.4×	54 0.7×	15 0.6×	15	1.1k
Christophe Gaillochet Germany	14	971 1.4×	788 1.4×	27 0.2×	26 0.3×	50 1.9×	17	1.1k
Kenji Osabe Japan	18	619 0.9×	395 0.7×	128 1.2×	21 0.3×	18 0.7×	35	743
Anupam Singh India	12	405 0.6×	181 0.3×	125 1.1×	59 0.8×	21 0.8×	49	518
Bojun Ma China	15	789 1.1×	430 0.8×	111 1.0×	90 1.2×	12 0.4×	37	924

Countries citing papers authored by Chunbo Miao

Since Specialization

Citations

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

Fields of papers citing papers by Chunbo Miao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunbo Miao

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

All Works

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16 of 16 papers shown

Li, Fei, Haonan Hou, Zhen Chen, et al.. (2025). Targeted insertion of large DNA fragments through template‐jumping prime editing in rice. Plant Biotechnology Journal. 23(7). 2645–2647. 4 indexed citations

Liu, Huixia, Pei Zhao, Kaiyuan Wang, et al.. (2024). SLAM: Structure-aware lysine β-hydroxybutyrylation prediction with protein language model. International Journal of Biological Macromolecules. 280(Pt 1). 135741–135741. 2 indexed citations

Zhao, Pei, Kaiyuan Wang, Huixia Liu, et al.. (2024). Current computational tools for protein lysine acylation site prediction. Briefings in Bioinformatics. 25(6). 3 indexed citations

Song, Minglei, Fei Li, Zhen Chen, et al.. (2024). Engineering high-frequency apomixis with normal seed production in hybrid rice. iScience. 27(12). 111479–111479. 4 indexed citations

Zhao, Pei, Fuyi Li, Junzhou Li, et al.. (2023). ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning. Briefings in Bioinformatics. 24(2). 6 indexed citations

Zhang, Xiaofan, Yuan Cheng, Sachin Teotia, et al.. (2023). The miR167-OsARF12 module regulates rice grain filling and grain size downstream of miR159. Plant Communications. 4(5). 100604–100604. 32 indexed citations

Zhang, Fanfan, Yi Shen, Chunbo Miao, et al.. (2020). OsRAD51D promotes homologous pairing and recombination by preventing nonhomologous interactions in rice meiosis. New Phytologist. 227(3). 824–839. 16 indexed citations

Zhang, Yan, et al.. (2020). Seed-Specific Overexpression of SPL12 and IPA1 Improves Seed Dormancy and Grain Size in Rice. Frontiers in Plant Science. 11. 532771–532771. 16 indexed citations

Miao, Chunbo, Zhen Wang, Lin Zhang, et al.. (2019). The grain yield modulator miR156 regulates seed dormancy through the gibberellin pathway in rice. Nature Communications. 10(1). 3822–3822. 141 indexed citations

10.

Miao, Chunbo, Dong Wang, Reqing He, Shenkui Liu, & Jian‐Kang Zhu. (2019). Mutations in MIR396e and MIR396f increase grain size and modulate shoot architecture in rice. Plant Biotechnology Journal. 18(2). 491–501. 89 indexed citations

11.

Miao, Chunbo, Lihong Xiao, Kai Hua, et al.. (2018). Mutations in a subfamily of abscisic acid receptor genes promote rice growth and productivity. Proceedings of the National Academy of Sciences. 115(23). 6058–6063. 250 indexed citations breakdown →

12.

Wu, Zhigang, Ding Tang, Kai Liu, et al.. (2018). Characterization of a new semi-dominant dwarf allele of SLR1 and its potential application in hybrid rice breeding. Journal of Experimental Botany. 69(20). 4703–4713. 39 indexed citations

13.

Tang, Ding, Chunbo Miao, Yafei Li, et al.. (2014). OsRAD51C is essential for double-strand break repair in rice meiosis. Frontiers in Plant Science. 5. 167–167. 38 indexed citations

14.

Miao, Chunbo, Ding Tang, Honggen Zhang, et al.. (2013). CENTRAL REGION COMPONENT1, a Novel Synaptonemal Complex Component, Is Essential for Meiotic Recombination Initiation in Rice. The Plant Cell. 25(8). 2998–3009. 82 indexed citations

15.

Wang, Kejian, Mo Wang, Ding Tang, et al.. (2012). The Role of Rice HEI10 in the Formation of Meiotic Crossovers. PLoS Genetics. 8(7). e1002809–e1002809. 113 indexed citations

16.

Wang, Mo, Ding Tang, Kejian Wang, et al.. (2011). OsSGO1 maintains synaptonemal complex stabilization in addition to protecting centromeric cohesion during rice meiosis. The Plant Journal. 67(4). 583–594. 44 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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