Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods

BACKGROUND: Alternative splicing (AS) plays critical roles in generating protein diversity and complexity. Dysregulation of AS underlies the initiation and progression of tumors. Machine learning approaches have emerged as efficient tools to identify promising biomarkers. It is meaningful to explore...

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Detalles Bibliográficos
Autores principales: Cai, Qidong, He, Boxue, Zhang, Pengfei, Zhao, Zhenyu, Peng, Xiong, Zhang, Yuqian, Xie, Hui, Wang, Xiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720605/
https://www.ncbi.nlm.nih.gov/pubmed/33287830
http://dx.doi.org/10.1186/s12967-020-02635-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720605/
https://www.ncbi.nlm.nih.gov/pubmed/33287830
http://dx.doi.org/10.1186/s12967-020-02635-y

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