Cargando…
Interpretation of convolutional neural networks reveals crucial sequence features involving in transcription during fiber development
BACKGROUND: Upland cotton provides the most natural fiber in the world. During fiber development, the quality and yield of fiber were influenced by gene transcription. Revealing sequence features related to transcription has a profound impact on cotton molecular breeding. We applied convolutional ne...
Autores principales: | Liu, Shang, Cheng, Hailiang, Ashraf, Javaria, Zhang, Youping, Wang, Qiaolian, Lv, Limin, He, Man, Song, Guoli, Zuo, Dongyun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922751/ https://www.ncbi.nlm.nih.gov/pubmed/35291940 http://dx.doi.org/10.1186/s12859-022-04619-9 |
Ejemplares similares
-
Genome-Wide Analysis of AAT Genes and Their Expression Profiling during Fiber Development in Cotton
por: Yang, Dongjie, et al.
Publicado: (2021) -
Functional characterization of the GhNRT2.1e gene reveals its significant role in improving nitrogen use efficiency in Gossypium hirsutum
por: Zhang, Xinmiao, et al.
Publicado: (2023) -
Genome-Wide Identification and Characterization of GhCOMT Gene Family during Fiber Development and Verticillium Wilt Resistance in Cotton
por: Wu, Cuicui, et al.
Publicado: (2021) -
Weighted Gene Co-Expression Network Analysis Reveals Hub Genes Contributing to Fuzz Development in Gossypium arboreum
por: Feng, Xiaoxu, et al.
Publicado: (2021) -
Identification of the CesA Subfamily and Functional Analysis of GhMCesA35 in Gossypium hirsutum L.
por: Zhao, Ruolin, et al.
Publicado: (2022)