Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach

BACKGROUND: Mutation processes leave different signatures in genes. For single-base substitutions, previous studies have suggested that mutation signatures are not only reflected in mutation bases but also in neighboring bases. However, because of the lack of a method to identify features of long se...

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Detalles Bibliográficos
Autores principales: Ji, Hongchen, Li, Junjie, Zhang, Qiong, Yang, Jingyue, Duan, Juanli, Wang, Xiaowen, Ma, Ben, Zhang, Zhuochao, Pan, Wei, Zhang, Hongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686331/
https://www.ncbi.nlm.nih.gov/pubmed/34930241
http://dx.doi.org/10.1186/s12920-021-01144-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686331/
https://www.ncbi.nlm.nih.gov/pubmed/34930241
http://dx.doi.org/10.1186/s12920-021-01144-1

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