Yufeng Yang
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Also affiliated: Zhengzhou University (2011–2024); Henan Academy of Agricultural Sciences (2018–2024); Ministry of Agriculture and Rural Affairs (2022); Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (2024); China Agricultural University (2017–2022); Zhejiang University (2024); Guangdong Ocean University (2024); Fuzhou University (2024)
Research Areas
Biomedical Subjects
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Biography and Research Information
OverviewAI-generated summary
Yufeng Yang's research focuses on understanding and enhancing plant responses to environmental stressors, particularly in sweet potato. His work investigates the genetic and molecular mechanisms underlying tolerance to challenges such as drought and cold stress. Yang has published studies identifying key genes, including WRKY transcription factors and bHLH genes, that play roles in conferring stress resistance. His research also utilizes integrated transcriptome and metabolome analyses to elucidate the complex molecular pathways involved in plant adaptation and defense against pathogens like stem nematodes. Further investigations explore the regulation of specific traits, such as sweet potato skin color, and extend to other plant species, examining salt tolerance mechanisms in cotton.
Metrics
- h-index: 10
- Publications: 20
- Citations: 269
Selected Publications
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RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.) (2026)
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Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20 (2019)
Collaboration Network
Top Collaborators
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- Transcript profiling for regulation of sweet potato skin color in Sushu8 and its mutant Zhengshu20
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
- RNA-seq meta-analysis and machine learning identify stress-responsive genes and improve genomic prediction in common bean ( Phaseolus vulgaris L.) with cross-species application in cowpea ( Vigna unguiculata L.)
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