Xianran Li
Wheat Health, Genetics, and Quality Research
Research Biologist
Phone: (509) 335-3620
Fax:
Room 281
WASHINGTON STATE UNIV
281 Clark Hall
PULLMAN,
WA
99164
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Publications
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Streamline unsupervised machine learning to survey and graph indel-based haplotypes from pan-genomes
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Zhang, B., Huang, H., Tibbs, L.E., Zhang, Z., Sanguinet, K., Vanous, A.E., Garland Campbell, K.A., Yu, J., Li, X. 2023. Streamline unsupervised machine learning to survey and graph indel-based haplotypes from pan-genomes. Molecular Plant. 16(6):975-978. https://doi.org/10.1016/j.molp.2023.05.005.
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An Independent Validation Reveals the Potential to Predict Hagberg-Perten Falling Number Using Spectrometers
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Chen, C., Hu, Y., Li, X., Cannon, A., Morris, C., Delwiche, S.R., Steber, C.M., Zhang, Z. 2023. An Independent Validation Reveals the Potential to Predict Hagberg-Perten Falling Number Using Spectrometers. The Plant Phenome Journal. 2023:6(1). https://doi.org/10.1002/ppj2.20070.
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Generation of sesame mutant population by mutagenesis and identification of high oleate mutants by GC analysis
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Wang, M.L., Tonnis, B.D., Li, X., Morris, J.B. 2023. Generation of sesame mutant population by mutagenesis and identification of high oleate mutants by GC analysis. Plants. 12(6). https://doi.org/10.3390/plants12061294.
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Machine learning for predicting phenotype from genotype and environment
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Guo, T., Li, X. 2023. Machine learning for predicting phenotype from genotype and environment. Current Opinion in Biotechnology. 79. Article 102853. https://doi.org/10.1016/j.copbio.2022.102853.
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Genomic prediction of tocochromanols in exotic-derived maize
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Tibbs-Cortes, L.E., Guo, T., Li, X., Tanaka, R., Vanous, A.E., Peters, D.W., Gardner, C.A., Magallanes-Lundback, M., Deason, N.T., DellaPenna, D., Gore, M.A., Yu, J. 2022. Genomic prediction of tocochromanols in exotic-derived maize. The Plant Genome. Article e20286. https://doi.org/10.1002/tpg2.20286.
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Leveraging prior biological knowledge improves prediction of tocochromanols in maize grain
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Tanaka, R., Wu, D., Li, X., Tibbs-Cortes, L.E., Wood, J., Magallanes-Lundback, M., Bornowski, N., Hamilton, J.P., Vaillancourt, B., Li, X., Deason, N.T., Schoenbaum, G.R., Buell, C.R., DellaPenna, D., Yu, J., Gore, M.A. 2022. Leveraging prior biological knowledge improves prediction of tocochromanols in maize grain. The Plant Genome. Article e20276. https://doi.org/10.1002/tpg2.20276.
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Evaluation of variability in seed coat color, weight, oil content, and fatty acid composition within the entire USDA-cultivated peanut germplasm collection
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Wang, M.L., Tonnis, B.D., Chen, C., Li, X., Pinnow, D.L., Tallury, S.P., Stigura, N.E., Pederson, G.A., Harrison, M.L. 2022. Evaluation of variability in seed coat color, weight, oil content, and fatty acid composition within the entire USDA-cultivated peanut germplasm collection. Crop Science. 62:2332-2346. https://doi.org/10.1002/csc2.20830.
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Combining GWAS and TWAS to identify candidate causal genes for tocochromanol levels in maize grain
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Wu, D., Li, X., Tanaka, R., Wood, J., Tibbs-Cortes, L., Magallanes-Lundback, M., Bornowski, N., Hamilton, J., Vaillancourt, B., Diepenbrock, C., Li, X., Deason, N., Schoenbaum, G., Yu, J., Buell, R., Dellapenna, D., Gore, M. 2022. Combining GWAS and TWAS to identify candidate causal genes for tocochromanol levels in maize grain. Genetics. 221(4). Article iyac091. https://doi.org/10.1093/genetics/iyac091.
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Unraveling the sorghum domestication
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Li, X., Yu, J. 2022. Unraveling the sorghum domestication. Molecular Plant. 15:1-2. https://doi.org/10.1016/j.molp.2022.03.006.
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Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range
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Mu, Q., Guo, T., Li, X., Yu, J. 2022. Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range. New Phytologist. 233(4):1768-1779. https://doi.org/10.1111/nph.17904.
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Genetics-inspired data-driven approaches explain and predict crop performance fluctuations attributed to changing climatic conditions
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Li, X., Guo, T., Bai, G., Zhang, Z., See, D.R., Marshall, J., Garland Campbell, K.A., Yu, J. 2022. Genetics-inspired data-driven approaches explain and predict crop performance fluctuations attributed to changing climatic conditions. Molecular Plant. 15(2):203-206. https://doi.org/10.1016/j.molp.2022.01.001.
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High-efficiency plastome base editing in rice with TAL cytosine deaminase
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Li, R., Char, S., Liu, B., Liu, H., Li, X., Yang, B. 2021. High-efficiency plastome base editing in rice with TAL cytosine deaminase. Molecular Plant. 14(9):1412-1414. https://doi.org/10.1016/j.molp.2021.07.007.
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ARS News Articles
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