Multitask Deep Neural Networks for Ames Mutagenicity Prediction-Reference-Cited by-同舟云学术

Multitask Deep Neural Networks for Ames Mutagenicity Prediction

Published:2022-09-06 Issue:24 Volume:62 Page:6342-6351
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Martínez María Jimena¹^ORCID,Sabando María Virginia²³^ORCID,Soto Axel J.²³^ORCID,Roca Carlos⁴^ORCID,Requena-Triguero Carlos⁴,Campillo Nuria E.⁴⁵^ORCID,Páez Juan A.⁶,Ponzoni Ignacio²³^ORCID

Affiliation:

1. ISISTAN (CONICET - UNCPBA) Campus Universitario - Paraje Arroyo Seco, 7000, Tandil, Argentina

2. Institute for Computer Science and Engineering, UNS-CONICET, 8000, Bahía Blanca, Argentina

3. Department of Computer Science and Engineering, Universidad Nacional del Sur, 8000, Bahía Blanca, Argentina

4. CIB Margarita Salas (CSIC) Ramiro de Maeztu, 9. 28740, Madrid, Spain

5. Instituto de Ciencias Matemáticas (CSIC), Nicolás Cabrera, no13-15, Campus de Cantoblanco, UAM, CP 28049, Madrid, Spain

6. Instituto de Química Médica. Consejo Superior de Investigaciones Científicas (CSIC), Juan de la Cierva 3, 28006, Madrid, Spain

Funder

Consejo Superior de Investigaciones Cient?ficas

Consejo Nacional de Investigaciones Cient?ficas y T?cnicas

Universidad Nacional del Sur

Fondo para la Investigaci?n Cient?fica y Tecnol?gica

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.2c00532

Reference39 articles.

1. An Improved Bacterial Test System for the Detection and Classification of Mutagens and Carcinogens

2. Revised methods for the Salmonella mutagenicity test

3. Could deep learning in neural networks improve the QSAR models?

4. Improvement of quantitative structure–activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project

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