Cargando…
A Knowledge-Based Discovery Approach Couples Artificial Neural Networks With Weight Engineering to Uncover Immune-Related Processes Underpinning Clinical Traits of Breast Cancer
Immune-related processes are important in underpinning the properties of clinical traits such as prognosis and drug response in cancer. The possibility to extract knowledge learned by artificial neural networks (ANNs) from omics data to explain cancer clinical traits is a very attractive subject for...
Autores principales: | Zhang, Cheng, Correia, Cristina, Weiskittel, Taylor M., Tan, Shyang Hong, Meng-Lin, Kevin, Yu, Grace T., Yao, Jingwen, Yeo, Kok Siong, Zhu, Shizhen, Ung, Choong Yong, Li, Hu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330471/ https://www.ncbi.nlm.nih.gov/pubmed/35911770 http://dx.doi.org/10.3389/fimmu.2022.920669 |
Ejemplares similares
-
SPIN-AI: A Deep Learning Model That Identifies Spatially Predictive Genes
por: Meng-Lin, Kevin, et al.
Publicado: (2023) -
Gene utility recapitulates chromosomal aberrancies in advanced stage neuroblastoma
por: Ung, Choong Y., et al.
Publicado: (2022) -
Uncovering Pharmacological Opportunities for Cancer Stem Cells—A Systems Biology View
por: Correia, Cristina, et al.
Publicado: (2022) -
Manifold epigenetics: A conceptual model that guides engineering strategies to improve whole-body regenerative health
por: Ung, Choong Yong, et al.
Publicado: (2023) -
De novo individualized disease modules reveal the synthetic penetrance of genes and inform personalized treatment regimens
por: Weiskittel, Taylor M., et al.
Publicado: (2022)