Huaqin He

1.1k total citations
45 papers, 816 citations indexed

About

Huaqin He is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Huaqin He has authored 45 papers receiving a total of 816 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 21 papers in Plant Science and 4 papers in Genetics. Recurrent topics in Huaqin He's work include Genomics and Phylogenetic Studies (10 papers), Bioinformatics and Genomic Networks (8 papers) and Machine Learning in Bioinformatics (6 papers). Huaqin He is often cited by papers focused on Genomics and Phylogenetic Studies (10 papers), Bioinformatics and Genomic Networks (8 papers) and Machine Learning in Bioinformatics (6 papers). Huaqin He collaborates with scholars based in China, United States and United Kingdom. Huaqin He's co-authors include Jiaxu Li, Tao Huan, Wei Liu, Xinhai Chen, Yongfei Wang, Shoukai Lin, Wenfeng Zhang, Jian Huang, Hua Ye and Ziding Zhang and has published in prestigious journals such as Scientific Reports, Biochemical and Biophysical Research Communications and International Journal of Molecular Sciences.

In The Last Decade

Huaqin He

44 papers receiving 795 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Huaqin He China 17 435 404 59 49 48 45 816
Haipeng Zhang China 18 535 1.2× 419 1.0× 35 0.6× 22 0.4× 18 0.4× 64 902
Christelle Guillier France 9 288 0.7× 298 0.7× 63 1.1× 10 0.2× 25 0.5× 13 629
Xiaoyi Zhu Australia 13 460 1.1× 319 0.8× 56 0.9× 11 0.2× 79 1.6× 25 861
Xue Bai China 19 498 1.1× 203 0.5× 28 0.5× 10 0.2× 94 2.0× 60 924
Barry Hon Cheung Wong China 13 694 1.6× 272 0.7× 40 0.7× 10 0.2× 21 0.4× 14 942
Dipanjana Ghosh India 8 250 0.6× 224 0.6× 49 0.8× 10 0.2× 15 0.3× 16 534
Yoshitaka Tomigahara Japan 14 627 1.4× 141 0.3× 19 0.3× 25 0.5× 187 3.9× 47 1.0k
Bing Bai China 19 378 0.9× 522 1.3× 56 0.9× 8 0.2× 23 0.5× 43 838
Nianshu Zhang United Kingdom 17 1.3k 2.9× 190 0.5× 137 2.3× 16 0.3× 111 2.3× 29 1.5k
Jitka Široká Czechia 13 319 0.7× 459 1.1× 46 0.8× 15 0.3× 15 0.3× 28 746

Countries citing papers authored by Huaqin He

Since Specialization
Citations

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

Fields of papers citing papers by Huaqin He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huaqin He

This figure shows the co-authorship network connecting the top 25 collaborators of Huaqin He. A scholar is included among the top collaborators of Huaqin He 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 Huaqin He. Huaqin He 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.
Wu, Shuhong, et al.. (2025). Piriformospora indica Enhances Rice Blast Resistance and Plant Growth. Agronomy. 15(1). 118–118. 1 indexed citations
2.
Liu, Wei, Huaqin He, & Davide Chicco. (2024). Gene signatures for cancer research: A 25-year retrospective and future avenues. PLoS Computational Biology. 20(10). e1012512–e1012512. 4 indexed citations
3.
Huang, Wei, Enda Yu, Min Ye, et al.. (2024). Lignan-rich extract from Cinnamomum camphora leaf attenuates metabolic syndrome by modulating glycolipid metabolism and gut microbiota in T2DM mice. Phytomedicine. 135. 156118–156118. 9 indexed citations
4.
Huan, Tao, Shoukai Lin, Xuan Chen, et al.. (2024). OsBRW1, a novel blast‐resistant gene, coded a NBS‐LRR protein to interact with OsSRFP1 to balance rice growth and resistance. Plant Biotechnology Journal. 23(1). 250–267. 4 indexed citations
5.
Zhao, M., et al.. (2023). AraPathogen2.0: An Improved Prediction of Plant–Pathogen Protein–Protein Interactions Empowered by the Natural Language Processing Technique. Journal of Proteome Research. 23(1). 494–499. 5 indexed citations
6.
Lin, Yao‐Cheng, et al.. (2023). Integrated ATAC-Seq and RNA-Seq Data Analysis to Reveal OsbZIP14 Function in Rice in Response to Heat Stress. International Journal of Molecular Sciences. 24(6). 5619–5619. 16 indexed citations
7.
Lin, Liping, et al.. (2020). Drug vector representation: a tool for drug similarity analysis. Molecular Genetics and Genomics. 295(4). 1055–1062. 3 indexed citations
8.
Liu, Wei, Yanan Wang, & Huaqin He. (2020). CoFly: A gene coexpression database for the fruit fly Drosophila melanogaster. Archives of Insect Biochemistry and Physiology. 105(1). e21693–e21693. 1 indexed citations
9.
Liu, Wei, Liping Lin, Siqi Liu, et al.. (2019). Gene co-expression network analysis identifies trait-related modules in Arabidopsis thaliana. Planta. 249(5). 1487–1501. 24 indexed citations
10.
Lin, Shoukai, Yang Zou, Tao Huan, et al.. (2019). Differential Expression Proteins Contribute to Race-Specific Resistant Ability in Rice (Oryza sativa L.). Plants. 8(2). 29–29. 5 indexed citations
11.
Yang, Shiping, Hong Li, Huaqin He, Yuan Zhou, & Ziding Zhang. (2017). Critical assessment and performance improvement of plant–pathogen protein–protein interaction prediction methods. Briefings in Bioinformatics. 20(1). 274–287. 42 indexed citations
12.
Lin, Shoukai, Qi Song, Tao Huan, et al.. (2015). Rice_Phospho 1.0: a new rice-specific SVM predictor for protein phosphorylation sites. Scientific Reports. 5(1). 11940–11940. 25 indexed citations
13.
14.
Wang, Yongfei, Shoukai Lin, Qi Song, et al.. (2014). Genome-wide identification of heat shock proteins (Hsps) and Hsp interactors in rice: Hsp70s as a case study. BMC Genomics. 15(1). 344–344. 57 indexed citations
15.
Chen, Xinhai, Shoukai Lin, Qiulin Liu, et al.. (2014). Expression and interaction of small heat shock proteins (sHsps) in rice in response to heat stress. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1844(4). 818–828. 71 indexed citations
16.
Wang, Yongfei, et al.. (2009). Evaluation of Protein Phosphorylation Site Predictors. Protein and Peptide Letters. 17(1). 64–69. 16 indexed citations
17.
He, Huaqin & Jiaxu Li. (2008). Proteomic analysis of phosphoproteins regulated by abscisic acid in rice leaves. Biochemical and Biophysical Research Communications. 371(4). 883–888. 41 indexed citations
18.
He, Huaqin, et al.. (2008). Differential regulation of proteins and phosphoproteins in rice under drought stress. Biochemical and Biophysical Research Communications. 379(1). 133–138. 95 indexed citations
19.
He, Hua, et al.. (2005). The differential analysis on allelochemicals extracted from root exudates in different allelopathic rice accessions.. 517–520. 2 indexed citations
20.
Liang, Kangjing, Wenxiong Lin, Zhixiong Chen, et al.. (2003). [Heterosis and genetic correlation analysis of rice (Oryza sativa L.) grain weight development under different environmental conditions].. PubMed. 14(12). 2200–4. 2 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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