Cargando…

Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology

There are currently 85,000 chemicals registered with the Environmental Protection Agency (EPA) under the Toxic Substances Control Act, but only a small fraction have measured toxicological data. To address this gap, high-throughput screening (HTS) and computational methods are vital. As part of one...

Descripción completa

Detalles Bibliográficos
Autores principales:	Green, Adrian J., Mohlenkamp, Martin J., Das, Jhuma, Chaudhari, Meenal, Truong, Lisa, Tanguay, Robyn L., Reif, David M.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2021
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8301607/ https://www.ncbi.nlm.nih.gov/pubmed/34214078 http://dx.doi.org/10.1371/journal.pcbi.1009135

Ejemplares similares

Leveraging a High-Throughput Screening Method to Identify Mechanisms of Individual Susceptibility Differences in a Genetically Diverse Zebrafish Model
por: Wallis, Dylan J., et al.
Publicado: (2022)

Disrupting adversarial transferability in deep neural networks
por: Wiedeman, Christopher, et al.
Publicado: (2022)

Tea Chrysanthemum Detection by Leveraging Generative Adversarial Networks and Edge Computing
por: Qi, Chao, et al.
Publicado: (2022)

Concurrent Evaluation of Mortality and Behavioral Responses: A Fast and Efficient Testing Approach for High-Throughput Chemical Hazard Identification
por: Thunga, Preethi, et al.
Publicado: (2021)

Advancing Toxicology Research Using In Vivo High Throughput Toxicology with Small Fish Models
por: Planchart, Antonio, et al.
Publicado: (2016)

Machine Learning Uncertainties with Adversarial Neural Networks
por: Galler, Peter
Publicado: (2019)

Machine learning uncertainties with adversarial neural networks
por: Englert, Christoph, et al.
Publicado: (2019)

Universal adversarial attacks on deep neural networks for medical image classification
por: Hirano, Hokuto, et al.
Publicado: (2021)

Robustness of Sparsely Distributed Representations to Adversarial Attacks in Deep Neural Networks
por: Sardar, Nida, et al.
Publicado: (2023)

Deep autoencoder-based behavioral pattern recognition outperforms standard statistical methods in high-dimensional zebrafish studies
por: Green, Adrian J., et al.
Publicado: (2023)

Improved Classification of White Blood Cells with the Generative Adversarial Network and Deep Convolutional Neural Network
por: Almezhghwi, Khaled, et al.
Publicado: (2020)

Semisupervised adversarial neural networks for single-cell classification
por: Kimmel, Jacob C., et al.
Publicado: (2021)

Current Landscape of Generative Adversarial Networks for Facial Deidentification in Dermatology: Systematic Review and Evaluation
por: Park, Christine, et al.
Publicado: (2022)

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)

DGCNN: deep convolutional generative adversarial network based convolutional neural network for diagnosis of COVID-19
por: Laddha, Saloni, et al.
Publicado: (2022)

Leveraging Neural Networks in Preclinical Alcohol Research
por: Smith, Lauren C., et al.
Publicado: (2020)

Decorrelated Jet Substructure Tagging using Adversarial Neural Networks
por: Shimmin, Chase Owen
Publicado: (2017)

Mass-decorrelated Xbb Tagger using Adversarial Neural Network
por: Chen, Shihlung
Publicado: (2022)

Water Cherenkov detector reconstruction by Generative Adversarial Neural networks
por: Grigolia, Giorgi
Publicado: (2021)

Transferability of features for neural networks links to adversarial attacks and defences
por: Kotyan, Shashank, et al.
Publicado: (2022)

Interpatient ECG Heartbeat Classification with an Adversarial Convolutional Neural Network
por: Zhang, Jing, et al.
Publicado: (2021)

Guiding the retraining of convolutional neural networks against adversarial inputs
por: Durán, Francisco, et al.
Publicado: (2023)

Leveraging uncertainty information from deep neural networks for disease detection
por: Leibig, Christian, et al.
Publicado: (2017)

Cross-species behavior analysis with attention-based domain-adversarial deep neural networks
por: Maekawa, Takuya, et al.
Publicado: (2021)

Adversarial robustness in deep neural networks based on variable attributes of the stochastic ensemble model
por: Qin, Ruoxi, et al.
Publicado: (2023)

A New Statistical Approach to Characterize Chemical-Elicited Behavioral Effects in High-Throughput Studies Using Zebrafish
por: Zhang, Guozhu, et al.
Publicado: (2017)

An improved genetic algorithm and its application in neural network adversarial attack
por: Yang, Dingming, et al.
Publicado: (2022)

A Lightweight Method for Defense Graph Neural Networks Adversarial Attacks
por: Qiao, Zhi, et al.
Publicado: (2022)

Adversarial attacks on spiking convolutional neural networks for event-based vision
por: Büchel, Julian, et al.
Publicado: (2022)

Dissociable Neural Representations of Adversarially Perturbed Images in Convolutional Neural Networks and the Human Brain
por: Zhang, Chi, et al.
Publicado: (2021)

Generating mobility networks with generative adversarial networks
por: Mauro, Giovanni, et al.
Publicado: (2022)

Generative adversarial network based synthetic data training model for lightweight convolutional neural networks
por: Rather, Ishfaq Hussain, et al.
Publicado: (2023)

Leveraging Multiple Data Streams for Prioritization of Mixtures for Hazard Characterization
por: Rivera, Brianna N., et al.
Publicado: (2022)

Image synthesis of effective atomic number images using a deep convolutional neural network-based generative adversarial network
por: Kawahara, Daisuke, et al.
Publicado: (2022)

High-throughput characterization of chemical-associated embryonic behavioral changes predicts teratogenic outcomes
por: Reif, David M., et al.
Publicado: (2015)

Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks
por: Hwang, Ren-Hung, et al.
Publicado: (2023)

Hands-on generative adversarial networks with Keras: your guide to implementing next-generation generative adversarial networks
por: Valle, Rafael
Publicado: (2019)

Adversarial Neural Network-based data-simulation corrections for jet-tagging at CMS
por: Fischer, Benjamin
Publicado: (2019)

Conditional Adversarial Domain Adaptation Neural Network for Motor Imagery EEG Decoding
por: Tang, Xingliang, et al.
Publicado: (2020)

Generative Adversarial Phonology: Modeling Unsupervised Phonetic and Phonological Learning With Neural Networks
por: Beguš, Gašper
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_3kjjh3igtfemls4nsqlgne880s