Changling Huang

1.6k total citations
35 papers, 844 citations indexed

About

Changling Huang is a scholar working on Genetics, Plant Science and Molecular Biology. According to data from OpenAlex, Changling Huang has authored 35 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Genetics, 23 papers in Plant Science and 6 papers in Molecular Biology. Recurrent topics in Changling Huang's work include Genetic Mapping and Diversity in Plants and Animals (23 papers), Genetics and Plant Breeding (13 papers) and Genetic and phenotypic traits in livestock (7 papers). Changling Huang is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (23 papers), Genetics and Plant Breeding (13 papers) and Genetic and phenotypic traits in livestock (7 papers). Changling Huang collaborates with scholars based in China, Mexico and Kenya. Changling Huang's co-authors include Hongwu Wang, Xiaojiao Hu, Yujin Wu, Zhifang Liu, Yunbi Xu, Kun Li, B. M. Prasanna, Michael Olsen, Chuanxiao Xie and Junjie Fu and has published in prestigious journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Changling Huang

34 papers receiving 833 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Changling Huang China 17 716 451 233 118 38 35 844
Xiangbo Zhang China 13 770 1.1× 221 0.5× 466 2.0× 71 0.6× 30 0.8× 33 934
Ming Hao China 15 856 1.2× 232 0.5× 276 1.2× 83 0.7× 16 0.4× 73 938
Gautam Saripalli India 16 773 1.1× 233 0.5× 154 0.7× 132 1.1× 18 0.5× 36 836
Joachim Eder Germany 12 469 0.7× 246 0.5× 256 1.1× 64 0.5× 44 1.2× 25 588
K. V. Prabhu India 13 613 0.9× 227 0.5× 149 0.6× 66 0.6× 10 0.3× 36 695
Youlin Peng China 14 618 0.9× 296 0.7× 177 0.8× 43 0.4× 14 0.4× 36 664
Xiaojiao Hu China 13 424 0.6× 270 0.6× 164 0.7× 70 0.6× 41 1.1× 21 509
Ricky J. Milne Australia 9 897 1.3× 132 0.3× 201 0.9× 68 0.6× 40 1.1× 14 930
Shinya Yoshida Japan 12 822 1.1× 481 1.1× 166 0.7× 36 0.3× 20 0.5× 23 962
Yijun Wang China 17 818 1.1× 173 0.4× 408 1.8× 64 0.5× 10 0.3× 39 889

Countries citing papers authored by Changling Huang

Since Specialization
Citations

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

Fields of papers citing papers by Changling Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changling Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Changling Huang. A scholar is included among the top collaborators of Changling Huang 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 Changling Huang. Changling Huang 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.
Wang, Jingxin, Liwei Liu, Kunhui He, et al.. (2025). Accurate genomic prediction for grain yield and grain moisture content of maize hybrids using multi‐environment data. Journal of Integrative Plant Biology. 67(5). 1379–1394. 1 indexed citations
2.
He, Kunhui, Tingxi Yu, Shang Gao, et al.. (2025). Leveraging Automated Machine Learning for Environmental Data‐Driven Genetic Analysis and Genomic Prediction in Maize Hybrids. Advanced Science. 12(17). e2412423–e2412423. 7 indexed citations
3.
Fu, Junjie, Huihui Li, Jochen C. Reif, et al.. (2022). Integration of genomic selection with doubled-haploid evaluation in hybrid breeding: From GS 1.0 to GS 4.0 and beyond. Molecular Plant. 15(4). 577–580. 25 indexed citations
4.
Wang, Daoping, Xiaojiao Hu, Bo Ma, et al.. (2021). Comparative proteomic analysis reveals that the Heterosis of two maize hybrids is related to enhancement of stress response and photosynthesis respectively. BMC Plant Biology. 21(1). 34–34. 21 indexed citations
5.
Qi, Xiantao, Jinjie Zhu, Changlin Liu, et al.. (2020). Genome Editing Enables Next-Generation Hybrid Seed Production Technology. Molecular Plant. 13(9). 1262–1269. 54 indexed citations
6.
Liu, Xiaogang, Xiaojiao Hu, Kun Li, et al.. (2020). Genetic mapping and genomic selection for maize stalk strength. BMC Plant Biology. 20(1). 196–196. 32 indexed citations
7.
Wang, Hongwu, Kun Li, Changling Huang, et al.. (2020). Phenotype analysis and gene mapping of small kernel 7 (smk7) mutant in maize. ACTA AGRONOMICA SINICA. 47(2). 285–293. 1 indexed citations
8.
Liu, Xiaogang, Hongwu Wang, Xiaojiao Hu, et al.. (2019). Improving Genomic Selection With Quantitative Trait Loci and Nonadditive Effects Revealed by Empirical Evidence in Maize. Frontiers in Plant Science. 10. 1129–1129. 31 indexed citations
9.
Xu, Yunbi, Xiaogang Liu, Junjie Fu, et al.. (2019). Enhancing Genetic Gain through Genomic Selection: From Livestock to Plants. Plant Communications. 1(1). 100005–100005. 175 indexed citations
10.
Xu, Cheng, Hongwei Zhang, Jianhao Sun, et al.. (2018). Genome-wide association study dissects yield components associated with low-phosphorus stress tolerance in maize. Theoretical and Applied Genetics. 131(8). 1699–1714. 41 indexed citations
11.
Hu, Xiaojiao, Hongwu Wang, Kun Li, et al.. (2017). Genome-wide proteomic profiling reveals the role of dominance protein expression in heterosis in immature maize ears. Scientific Reports. 7(1). 16130–16130. 21 indexed citations
12.
Wang, Hongwu, Kun Li, Xiaojiao Hu, et al.. (2016). Genome-wide association analysis of forage quality in maize mature stalk. BMC Plant Biology. 16(1). 227–227. 42 indexed citations
13.
Hu, Xiaojiao, Hongwu Wang, Zhifang Liu, et al.. (2016). Transcriptome profiling and comparison of maize ear heterosis during the spikelet and floret differentiation stages. BMC Genomics. 17(1). 959–959. 37 indexed citations
14.
Li, Kun, Hongwu Wang, Xiaojiao Hu, et al.. (2016). Genome-Wide Association Study Reveals the Genetic Basis of Stalk Cell Wall Components in Maize. PLoS ONE. 11(8). e0158906–e0158906. 44 indexed citations
15.
Huang, Changling. (2011). Effects on Agronomic Characteristics and Yield of Maize Planting Density. Yumi kexue. 3 indexed citations
16.
Li, Yanyan, et al.. (2010). Relationship of root and stem characters with lodging resistance of summer maize.. He'nan nongye kexue. 20–22. 5 indexed citations
17.
Li, Yanyan, et al.. (2010). Enlightenment of Maize Breeding from Pioneer USA. Yumi kexue. 18(2). 133–135. 1 indexed citations
18.
Huang, Changling. (2010). Primary Study on Correlation Between Corn Variety Lodging Resistances and Its Stem Puncture-Pull Strength. Yumi kexue. 5 indexed citations
19.
Huang, Changling. (2010). Contribution Evaluation of Heterosis Effect to Chinese Maize Breeding.
20.
Huang, Changling. (2009). Effects of Chemical Regulation on Lodging and Yield of Maize. Yumi kexue. 3 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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