Cargando…
Identifying potential drug-target interactions based on ensemble deep learning
INTRODUCTION: Drug-target interaction prediction is one important step in drug research and development. Experimental methods are time consuming and laborious. METHODS: In this study, we developed a novel DTI prediction method called EnGDD by combining initial feature acquisition, dimensional reduct...
Autores principales: | Zhou, Liqian, Wang, Yuzhuang, Peng, Lihong, Li, Zejun, Luo, Xueming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10309650/ https://www.ncbi.nlm.nih.gov/pubmed/37396659 http://dx.doi.org/10.3389/fnagi.2023.1176400 |
Ejemplares similares
-
Deep Convolutional Neural Networks With Ensemble Learning and Generative Adversarial Networks for Alzheimer’s Disease Image Data Classification
por: Logan, Robert, et al.
Publicado: (2021) -
Identification of Potential Driver Genes and Pathways Based on Transcriptomics Data in Alzheimer's Disease
por: Xia, Liang-Yong, et al.
Publicado: (2022) -
Deep learning approaches for noncoding variant prioritization in neurodegenerative diseases
por: Lan, Alexander Y., et al.
Publicado: (2022) -
Multimodal Deep Learning Models for Detecting Dementia From Speech and Transcripts
por: Ilias, Loukas, et al.
Publicado: (2022) -
DeepParcellation: A novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians
por: Lim, Eun-Cheon, et al.
Publicado: (2022)