Searching for protein variants with desired properties using deep generative models.

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第一作者： Yan,Li

第一单位： School of Information, Yunnan Normal University, Kunming, China.

作者： Yan,Li ^[1] ; Yinying,Yao ^[2] ; Yu,Xia ^[1] ; Mingjing,Tang ^[3]

作者单位： School of Information, Yunnan Normal University, Kunming, China. ^[1] National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research, Huazhong Agricultural University, Wuhan, China.;Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China. ^[2] Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Yunnan Normal University, Kunming, China. tmj@ynnu.edu.cn.;School of Life Science, Yunnan Normal University, Kunming, China. tmj@ynnu.edu.cn. ^[3]

关键词 Deep generative model Protein engineering Temporal convolutional network Variational autoencoder

主题词人类(Humans);突变蛋白质类(Mutant Proteins);氨基酸序列(Amino Acid Sequence);氨基酸类(Amino Acids);生物进化(Biological Evolution);学习(Learning)

DOI 10.1186/s12859-023-05415-9

PMID 37480001

发布时间 2024-09-29

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准确一般字义偏差语意偏离译文作用小提交