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Institute of Crop Sciences,
Chinese Academy of Agricultural Sciences, Beijing 100081, China
E-mail: lihuihui@caas.cn
https://caas.teacher.360eol.com/teacherBasic/preview?teacherId=26510
Area of expertise: statistical genomics and genetics, genomic prediction, gene mapping, artificial intelligence, smart breeding
Selected Publications:
Li, H., Li, X., Zhang, P., Feng, Y., Mi, J., Gao, S., Sheng, L., Ali, M., Yang, Z., Li, L., Fang, W., Wang, W., Qian, Q., Gu, F., and Zhou, W. (2024). Smart Breeding Platform: A web-based tool for high-throughput population genetics, phenomics, and genomic selection. Mol. Plant 17:677–681.
Chen, S., Du, T., Huang, Z., He, K., Yang, M., Gao, S., Yu, T., Zhang, H., Li, X., Chen, S., Liu, C. M., and Li, H. (2024). The Spartina alterniflora genome sequence provides insights into the salt-tolerance mechanisms of exo-recretohalophytes. Plant Biotechnol. J. doi: 10.1111/pbi.14368.
Wang, K., Abid, M. A., Rasheed, A., Crossa, J., Hearne, S., and Li, H. (2023). DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants. Mol. Plant 16:279–293.
Maqbool, S., Naseer, S., Zahra, N., Rasool, F., Qayyum, H., Majeed, K., Jahanzaib, M., Sajjad, M., Fayyaz, M., Naeem, M. K., Khan, M. R., Zhang, H., Rasheed, A., and Li, H. (2023). RNAseq of diverse spring wheat cultivars released during last 110 years. Sci. Data 10:884.
Yang, M., Chen, S., Huang, Z., Gao, S., Yu, T., Du, T., Zhang, H., Li, X., Liu, C. M., Chen, S., and Li, H. (2023) Deep learning-enabled discovery and characterization of HKT genes in Spartina alterniflora. Plant J. 116:690–705.
Li, H., and He, Z. (2021) Warming climate challenges breeding. Nat. Plants 7:1164–1165.
Li, J., Li, D., Espinosa, C. Z., Pastor, V. T., Rasheed, A., Rojas, N. P., Wang, J., Varela, A. S., Carolina de Almeida Silva, N., Schnable, P. S., Costich, D. E., and Li, H. (2021) Genome-wide analyses reveal footprints of divergent selection and popping-related traits in CIMMYT's maize inbred lines. J. Exp. Bot. 72:1307–1320.
Li, J., Chen, G. B., Rasheed, A., Li, D., Sonder, K., Zavala Espinosa, C., Wang, J., Costich, D. E., Schnable, P. S., Hearne, S. J., and Li, H. (2019) Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS. Mol. Ecol. 28:3544–3560.
Li, H., Rasheed, A., Hickey, L.T., and He, Z. (2018) Fast-forwarding genetic gain. Trends Plant Sci. 23:184–186.
Selected Registered Patents
Li H, Yu T. and He K. A machine learning-based analyzing tool for genotype and environment interaction and its application. ZL 202410245774.4, (2024.05.28), China.
Li H, Wang K. A deep learning-based genomic prediction method. ZL202311218507.X, (2023.12.12), China.
Li H, Huang Z, Gao S, Feng Y. A processing method for filtering and selecting breeding data. ZL202311041546.7, (2023.11.07), China.
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