Xiaoding Ma

1.7k total citations · 1 hit paper
54 papers, 1.1k citations indexed

About

Xiaoding Ma is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Xiaoding Ma has authored 54 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Plant Science, 38 papers in Genetics and 15 papers in Molecular Biology. Recurrent topics in Xiaoding Ma's work include Genetic Mapping and Diversity in Plants and Animals (38 papers), GABA and Rice Research (23 papers) and Rice Cultivation and Yield Improvement (21 papers). Xiaoding Ma is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (38 papers), GABA and Rice Research (23 papers) and Rice Cultivation and Yield Improvement (21 papers). Xiaoding Ma collaborates with scholars based in China, South Korea and United States. Xiaoding Ma's co-authors include Longzhi Han, Di Cui, Guilan Cao, Jiulin Wang, Zhijun Cheng, Xiuping Guo, Bing Han, Yongli Qiao, Fuqing Wu and Cailin Lei and has published in prestigious journals such as Science, Molecular Cell and PLoS ONE.

In The Last Decade

Xiaoding Ma

52 papers receiving 1.1k citations

Hit Papers

Enhancing rice panicle branching and grain yield through ... 2024 2026 2025 2024 10 20 30 40
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. Enhancing rice panicle branching and grain yield through tissue-specific brassinosteroid inhibition
    2024 44 citations Xiaoding Ma et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaoding Ma China 18 910 413 336 42 36 54 1.1k
Wang‐Wei Ye China 12 1.1k 1.2× 497 1.2× 466 1.4× 32 0.8× 25 0.7× 15 1.2k
Samart Wanchana Thailand 19 733 0.8× 202 0.5× 222 0.7× 52 1.2× 43 1.2× 52 851
Huilong Du China 15 1.2k 1.3× 414 1.0× 665 2.0× 42 1.0× 27 0.8× 31 1.5k
Tetsuya Nakazaki Japan 18 872 1.0× 141 0.3× 432 1.3× 39 0.9× 54 1.5× 59 1.0k
Moju Cao China 15 814 0.9× 366 0.9× 376 1.1× 18 0.4× 28 0.8× 45 997
Jason D. Gillman United States 21 1.1k 1.2× 214 0.5× 359 1.1× 62 1.5× 16 0.4× 46 1.3k
Sandip M. Kale India 24 1.4k 1.5× 236 0.6× 326 1.0× 39 0.9× 35 1.0× 42 1.5k
Qing Ji China 13 708 0.8× 327 0.8× 342 1.0× 46 1.1× 16 0.4× 36 896
Guanqing Jia China 16 844 0.9× 273 0.7× 401 1.2× 46 1.1× 14 0.4× 62 1.0k
Zhangxiong Liu China 20 1.2k 1.4× 219 0.5× 211 0.6× 40 1.0× 15 0.4× 72 1.4k

Countries citing papers authored by Xiaoding Ma

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoding Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoding Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoding Ma. A scholar is included among the top collaborators of Xiaoding Ma 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 Xiaoding Ma. Xiaoding Ma 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.
Liu, Jin, et al.. (2025). Candidate gene discovery for nitrogen use efficiency in rice based on genome-wide association study. Current Plant Biology. 42. 100479–100479.
2.
Wang, Haolin, Xiangzheng Fu, Lijia Liu, et al.. (2025). PhytoCluster: a generative deep learning model for clustering plant single-cell RNA-seq data. aBIOTECH. 6(2). 189–201. 1 indexed citations
3.
4.
Xia, Duo, Peizhou Xu, Shuqin Zheng, et al.. (2025). Haplotype Analysis of the GL7/GW7/SLG7 Gene and Its Application in Improving the Grain Quality of Three-Line Hybrid Rice. Rice. 18(1). 38–38. 2 indexed citations
5.
Ma, Xiaoding, Jianli Yin, Yang Zhou, et al.. (2024). A programmable targeted protein-degradation platform for versatile applications in mammalian cells and mice. Molecular Cell. 84(8). 1585–1600.e7. 15 indexed citations
6.
Ma, Xiaoding, Shengyang Wu, Di Cui, et al.. (2024). DeepCCR: large‐scale genomics‐based deep learning method for improving rice breeding. Plant Biotechnology Journal. 22(10). 2691–2693. 19 indexed citations
7.
8.
Zhang, Wei, Xiaoding Ma, Di Cui, et al.. (2023). Integrating linkage mapping and comparative transcriptome analysis for discovering candidate genes associated with salt tolerance in rice. Frontiers in Plant Science. 14. 1065334–1065334. 17 indexed citations
9.
Liu, Chunhui, Yanjie Wang, Xiaoding Ma, et al.. (2022). Traditional agricultural management of Kam Sweet Rice (Oryza sativa L.) in southeast Guizhou Province, China. Journal of Ethnobiology and Ethnomedicine. 18(1). 30–30. 12 indexed citations
10.
Zhang, Lina, et al.. (2022). Comparative analysis of rice reveals insights into the mechanism of colored rice via widely targeted metabolomics. Food Chemistry. 399. 133926–133926. 58 indexed citations
11.
Han, Bing, et al.. (2021). Evidence for evolution and selection of drought-resistant genes based on high-throughput resequencing in weedy rice. Journal of Experimental Botany. 73(7). 1949–1962. 8 indexed citations
12.
13.
Han, Bing, et al.. (2020). Parallel reaction monitoring revealed tolerance to drought proteins in weedy rice (Oryza sativa f. spontanea). Scientific Reports. 10(1). 12935–12935. 8 indexed citations
14.
Han, Bing, Xiaoding Ma, Di Cui, et al.. (2020). Comprehensive Evaluation and Analysis of the Mechanism of Cold Tolerance Based on the Transcriptome of Weedy Rice Seedlings. Rice. 13(1). 12–12. 32 indexed citations
15.
16.
Ma, Xiaoding, et al.. (2019). FLA, which encodes a homolog of UBP, is required for chlorophyll accumulation and development of lemma and palea in rice. Plant Cell Reports. 38(3). 321–331. 7 indexed citations
17.
Wang, Yanjie, et al.. (2018). Status and factors influencing on-farm conservation of Kam Sweet Rice (Oryza sativa L.) genetic resources in southeast Guizhou Province, China. Journal of Ethnobiology and Ethnomedicine. 14(1). 76–76. 30 indexed citations
18.
Ma, Jian, Xiaoding Ma, Zhichao Zhao, et al.. (2015). Development and Application of a Functional Marker of the Blast Resistance Gene Pi35 in Rice. ACTA AGRONOMICA SINICA. 41(12). 1779–1790. 3 indexed citations
19.
Ma, Xiaoding, Jian Ma, Honghong Zhai, et al.. (2015). CHR729 Is a CHD3 Protein That Controls Seedling Development in Rice. PLoS ONE. 10(9). e0138934–e0138934. 37 indexed citations
20.
Ma, Xiaoding, Chaozhu Xing, Liping Guo, et al.. (2007). Analysis of Differentially Expressed Genes in Genic Male Sterility Cotton (Gossypium hirsutum L.) Using cDNA-AFLP. Journal of genetics and genomics. 34(6). 536–543. 15 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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