Cargando…

Prediction of Drug-Likeness Using Deep Autoencoder Neural Networks

Due to diverse reasons, most drug candidates cannot eventually become marketed drugs. Developing reliable computational methods for prediction of drug-likeness of candidate compounds is of vital importance to improve the success rate of drug discovery and development. In this study, we used a fully...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hu, Qiwan, Feng, Mudong, Lai, Luhua, Pei, Jianfeng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2018
Materias:	Genetics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6277570/ https://www.ncbi.nlm.nih.gov/pubmed/30538725 http://dx.doi.org/10.3389/fgene.2018.00585

Ejemplares similares

Drug-protein interaction prediction via variational autoencoders and attention mechanisms
por: Zhang, Yue, et al.
Publicado: (2022)

GADTI: Graph Autoencoder Approach for DTI Prediction From Heterogeneous Network
por: Liu, Zhixian, et al.
Publicado: (2021)

Deep Autoencoder Neural Networks for Short-Term Traffic Congestion Prediction of Transportation Networks
por: Zhang, Sen, et al.
Publicado: (2019)

Deciphering tissue heterogeneity from spatially resolved transcriptomics by the autoencoder-assisted graph convolutional neural network
por: Li, Xinxing, et al.
Publicado: (2023)

Single-cell RNA-seq data analysis using graph autoencoders and graph attention networks
por: Feng, Xiang, et al.
Publicado: (2022)

Autoencoder Based Feature Selection Method for Classification of Anticancer Drug Response
por: Xu, Xiaolu, et al.
Publicado: (2019)

Structure-based de novo drug design using 3D deep generative models
por: Li, Yibo, et al.
Publicado: (2021)

Predicting Parkinson's Disease Genes Based on Node2vec and Autoencoder
por: Peng, Jiajie, et al.
Publicado: (2019)

deepDriver: Predicting Cancer Driver Genes Based on Somatic Mutations Using Deep Convolutional Neural Networks
por: Luo, Ping, et al.
Publicado: (2019)

Interpretable Feature Generation in ECG Using a Variational Autoencoder
por: Kuznetsov, V. V., et al.
Publicado: (2021)

Deep Recurrent Neural Network-Based Autoencoders for Acoustic Novelty Detection
por: Marchi, Erik, et al.
Publicado: (2017)

Deep Sparse Autoencoder and Recursive Neural Network for EEG Emotion Recognition
por: Li, Qi, et al.
Publicado: (2022)

Phenotype Prediction and Genome-Wide Association Study Using Deep Convolutional Neural Network of Soybean
por: Liu, Yang, et al.
Publicado: (2019)

CavityPlus: a web server for protein cavity detection with pharmacophore modelling, allosteric site identification and covalent ligand binding ability prediction
por: Xu, Youjun, et al.
Publicado: (2018)

Deep Convolutional Neural Network with Deconvolution and a Deep Autoencoder for Fault Detection and Diagnosis
por: Kanno, Yasuhiro, et al.
Publicado: (2022)

Sequence-based prediction of protein protein interaction using a deep-learning algorithm
por: Sun, Tanlin, et al.
Publicado: (2017)

Using autoencoders as a weight initialization method on deep neural networks for disease detection
por: Ferreira, Mafalda Falcão, et al.
Publicado: (2020)

EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder
por: Liu, Junxiu, et al.
Publicado: (2020)

miDruglikeness: Subdivisional Drug-Likeness Prediction Models Using Active Ensemble Learning Strategies
por: Cai, Chenjing, et al.
Publicado: (2022)

Anomaly detection in radiotherapy plans using deep autoencoder networks
por: Huang, Peng, et al.
Publicado: (2023)

A Novel Deep Neural Network Model for Multi-Label Chronic Disease Prediction
por: Zhang, Xiaoqing, et al.
Publicado: (2019)

Denoising of Optics Measurements Using Autoencoder Neural Networks
por: Fol, Elena, et al.
Publicado: (2021)

A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction
por: Deng, Lei, et al.
Publicado: (2017)

Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
por: Jung, Yuyeon, et al.
Publicado: (2022)

SAEROF: an ensemble approach for large-scale drug-disease association prediction by incorporating rotation forest and sparse autoencoder deep neural network
por: Jiang, Han-Jing, et al.
Publicado: (2020)

Repositioning Drugs to the Mitochondrial Fusion Protein 2 by Three-Tunnel Deep Neural Network for Alzheimer's Disease
por: Wang, Xun, et al.
Publicado: (2021)

Predicting lncRNA-protein interactions with bipartite graph embedding and deep graph neural networks
por: Ma, Yuzhou, et al.
Publicado: (2023)

A Deep Neural Network for Identifying DNA N4-Methylcytosine Sites
por: Zeng, Feng, et al.
Publicado: (2020)

Path-ATT-CNN: A Novel Deep Neural Network Method for Key Pathway Identification of Lung Cancer
por: Yuan, Lin, et al.
Publicado: (2022)

Representation Learning: Recommendation With Knowledge Graph via Triple-Autoencoder
por: Geng, Yishuai, et al.
Publicado: (2022)

Predicting Drug Synergy and Discovering New Drug Combinations Based on a Graph Autoencoder and Convolutional Neural Network
por: Li, Huijun, et al.
Publicado: (2023)

Using Local Convolutional Neural Networks for Genomic Prediction
por: Pook, Torsten, et al.
Publicado: (2020)

Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network
por: Peng, Lihong, et al.
Publicado: (2023)

Anomaly Detection for Sensor Signals Utilizing Deep Learning Autoencoder-Based Neural Networks
por: Esmaeili, Fatemeh, et al.
Publicado: (2023)

Breast cancer detection: Shallow convolutional neural network against deep convolutional neural networks based approach
por: Das, Himanish Shekhar, et al.
Publicado: (2023)

Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice
por: Simidjievski, Nikola, et al.
Publicado: (2019)

COVID-DeepPredictor: Recurrent Neural Network to Predict SARS-CoV-2 and Other Pathogenic Viruses
por: Saha, Indrajit, et al.
Publicado: (2021)

Prediction of Protein–Protein Interactions in Arabidopsis, Maize, and Rice by Combining Deep Neural Network With Discrete Hilbert Transform
por: Pan, Jie, et al.
Publicado: (2021)

Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach
por: Li, Rumeng, et al.
Publicado: (2019)

Developing an Embedding, Koopman and Autoencoder Technologies-Based Multi-Omics Time Series Predictive Model (EKATP) for Systems Biology research
por: Liu, Suran, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_ko5kj99osedekc4bj61fll7s0s