Cargando…

Explainable deep neural networks for novel viral genome prediction

Viral infection causes a wide variety of human diseases including cancer and COVID-19. Viruses invade host cells and associate with host molecules, potentially disrupting the normal function of hosts that leads to fatal diseases. Novel viral genome prediction is crucial for understanding the complex...

Descripción completa

Detalles Bibliográficos
Autores principales:	Dasari, Chandra Mohan, Bhukya, Raju
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer US 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232563/ https://www.ncbi.nlm.nih.gov/pubmed/34764607 http://dx.doi.org/10.1007/s10489-021-02572-3

Ejemplares similares

Predicting novel drug candidates against Covid-19 using generative deep neural networks
por: Amilpur, Santhosh, et al.
Publicado: (2022)

Comparative analysis of protein synthesis rate in COVID-19 with other human coronaviruses
por: Dasari, Chandra Mohan, et al.
Publicado: (2020)

Explaining decisions of deep neural networks used for fish age prediction
por: Ordoñez, Alba, et al.
Publicado: (2020)

Combination of deep neural network with attention mechanism enhances the explainability of protein contact prediction
por: Chen, Chen, et al.
Publicado: (2021)

Explaining deep neural networks for knowledge discovery in electrocardiogram analysis
por: Hicks, Steven A., et al.
Publicado: (2021)

Explainability of deep neural networks for MRI analysis of brain tumors
por: Zeineldin, Ramy A., et al.
Publicado: (2022)

Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks
por: Shickel, Benjamin, et al.
Publicado: (2023)

MGraphDTA: deep multiscale graph neural network for explainable drug–target binding affinity prediction
por: Yang, Ziduo, et al.
Publicado: (2022)

Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data
por: Bourgeais, Victoria, et al.
Publicado: (2021)

Explainable Multilayer Graph Neural Network for cancer gene prediction
por: Chatzianastasis, Michail, et al.
Publicado: (2023)

XMR: an explainable multimodal neural network for drug response prediction
por: Wang, Zihao, et al.
Publicado: (2023)

XAI-FR: Explainable AI-Based Face Recognition Using Deep Neural Networks
por: Rajpal, Ankit, et al.
Publicado: (2022)

Evaluating explainability for graph neural networks
por: Agarwal, Chirag, et al.
Publicado: (2023)

Quantitative evaluation of explainable graph neural networks for molecular property prediction
por: Rao, Jiahua, et al.
Publicado: (2022)

Explainable Brain Age Prediction using coVariance Neural Networks
por: Sihag, Saurabh, et al.
Publicado: (2023)

Life-threatening ventricular arrhythmia prediction in patients with dilated cardiomyopathy using explainable electrocardiogram-based deep neural networks( )
por: Sammani, Arjan, et al.
Publicado: (2022)

Predicting length of stay ranges by using novel deep neural networks
por: Zou, Hong, et al.
Publicado: (2023)

COVID-19 Automatic Diagnosis With Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks
Publicado: (2021)

Predicting potentially hazardous chemical reactions using an explainable neural network
por: Kim, Juhwan, et al.
Publicado: (2021)

Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders( )
por: van de Leur, Rutger R, et al.
Publicado: (2022)

Interpreting Deep Neural Networks and their Predictions
por: Samek, Wojciech
Publicado: (2018)

Explainable deep learning for tumor dynamic modeling and overall survival prediction using Neural-ODE
por: Laurie, Mark, et al.
Publicado: (2023)

Artificial neural networks applied for predicting and explaining the education level of Twitter users
por: Florea, Alexandru Razvan, et al.
Publicado: (2021)

Remaining Useful Life Prognosis for Turbofan Engine Using Explainable Deep Neural Networks with Dimensionality Reduction
por: Hong, Chang Woo, et al.
Publicado: (2020)

Enhancing Clinical Data Analysis by Explaining Interaction Effects between Covariates in Deep Neural Network Models
por: Shao, Yijun, et al.
Publicado: (2023)

Explainable graph neural networks for organic cages
por: Yuan, Qi, et al.
Publicado: (2022)

Identifying genomic islands with deep neural networks
por: Assaf, Rida, et al.
Publicado: (2021)

Explainable drug side effect prediction via biologically informed graph neural network
por: Huang, Tongtong, et al.
Publicado: (2023)

Deep neural network prediction of genome-wide transcriptome signatures – beyond the Black-box
por: Magnusson, Rasmus, et al.
Publicado: (2022)

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments
por: Jozwik, Kamila M., et al.
Publicado: (2017)

Predicting enhancers with deep convolutional neural networks
por: Min, Xu, et al.
Publicado: (2017)

Explaining Neural Networks Using Attentive Knowledge Distillation
por: Lee, Hyeonseok, et al.
Publicado: (2021)

Splice2Deep: An ensemble of deep convolutional neural networks for improved splice site prediction in genomic DNA
por: Albaradei, Somayah, et al.
Publicado: (2020)

Deep neural networks for accurate predictions of crystal stability
por: Ye, Weike, et al.
Publicado: (2018)

Integrating Explainability into Graph Neural Network Models for the Prediction of X-ray Absorption Spectra
por: Kotobi, Amir, et al.
Publicado: (2023)

Explaining compound activity predictions with a substructure-aware loss for graph neural networks
por: Amara, Kenza, et al.
Publicado: (2023)

Predicting drug response of tumors from integrated genomic profiles by deep neural networks
por: Chiu, Yu-Chiao, et al.
Publicado: (2019)

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

Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification
por: Böhle, Moritz, et al.
Publicado: (2019)

Explainability agreement between dermatologists and five visual explanations techniques in deep neural networks for melanoma AI classification
por: Giavina-Bianchi, Mara, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_8ld8jrq9ljngolf6nu6i1mjq58