Cargando…
A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data
Drug-induced toxicity damages the health and is one of the key factors causing drug withdrawal from the market. It is of great significance to identify drug-induced target-organ toxicity, especially the detailed pathological findings, which are crucial for toxicity assessment, in the early stage of...
Autores principales: | Su, Ran, Yang, Haitang, Wei, Leyi, Chen, Siqi, Zou, Quan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451100/ https://www.ncbi.nlm.nih.gov/pubmed/36070305 http://dx.doi.org/10.1371/journal.pcbi.1010402 |
Ejemplares similares
-
Predicting drug side effects by multi-label learning and ensemble learning
por: Zhang, Wen, et al.
Publicado: (2015) -
Integration of Next-Generation Sequencing Based Multi-Omics Approaches in Toxicogenomics
por: Jayapal, Manikandan
Publicado: (2012) -
iDNA-ABF: multi-scale deep biological language learning model for the interpretable prediction of DNA methylations
por: Jin, Junru, et al.
Publicado: (2022) -
mlDEEPre: Multi-Functional Enzyme Function Prediction With Hierarchical Multi-Label Deep Learning
por: Zou, Zhenzhen, et al.
Publicado: (2019) -
Toxicogenomics Data: The Road to Acceptance
por: Freeman, Kris
Publicado: (2004)