Large-Scale Integrative Analysis of Soybean Transcriptome Using an Unsupervised Autoencoder Model

Plant tissues are distinguished by their gene expression patterns, which can help identify tissue-specific highly expressed genes and their differential functional modules. For this purpose, large-scale soybean transcriptome samples were collected and processed starting from raw sequencing reads in...

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Vydáno v:	Frontiers in plant science Ročník 13; s. 831204
Hlavní autoři:	Su, Lingtao, Xu, Chunhui, Zeng, Shuai, Su, Li, Joshi, Trupti, Stacey, Gary, Xu, Dong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Media SA 03.03.2022 Frontiers Media S.A
Témata:	autoencoder Biological effects Data compression Datasets deep learning Gene expression gene regulatory network Genes Genomes Heterogeneity Modules Plant Science Plant tissues Source code soybean Soybeans Statistical power tissue-specific gene Transcription factors transcriptome analysis Transcriptomes functional module soybean deep learning autoencoder transcriptome analysis gene regulatory network tissue-specific gene
ISSN:	1664-462X, 1664-462X
On-line přístup:	Získat plný text
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