Cargando…
LSnet: detecting and genotyping deletions using deep learning network
The role and biological impact of structural variation (SV) are increasingly evident. Deletion accounts for 40% of SV and is an important type of SV. Therefore, it is of great significance to detect and genotype deletions. At present, high accurate long reads can be obtained as HiFi reads. And, thro...
Autores principales: | Luo, Junwei, Gao, Runtian, Chang, Wenjing, Wang, Junfeng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301831/ https://www.ncbi.nlm.nih.gov/pubmed/37388936 http://dx.doi.org/10.3389/fgene.2023.1189775 |
Ejemplares similares
-
INSnet: a method for detecting insertions based on deep learning network
por: Gao, Runtian, et al.
Publicado: (2023) -
BreakNet: detecting deletions using long reads and a deep learning approach
por: Luo, Junwei, et al.
Publicado: (2021) -
MI_DenseNetCAM: A Novel Pan-Cancer Classification and Prediction Method Based on Mutual Information and Deep Learning Model
por: Wang, Jianlin, et al.
Publicado: (2021) -
Genotype-phenotype correlation of deletions and duplications of 4p: case reports and literature review
por: Zhang, Xuan, et al.
Publicado: (2023) -
Plant Genotype to Phenotype Prediction Using Machine Learning
por: Danilevicz, Monica F., et al.
Publicado: (2022)