Li, Yaqin; Xu, Yongjin; Yu, Yi published an article in 2021, the title of the article was CRNNTL: Convolutional Recurrent Neural Network and Transfer Learning for QSAR Modeling in Organic Drug and Material Discovery.Product Details of 111-29-5 And the article contains the following content:
Mol. latent representations, derived from autoencoders (AEs), have been widely used for drug or material discovery over the past couple of years. In particular, a variety of machine learning methods based on latent representations have shown excellent performance on quant. structure-activity relationship (QSAR) modeling. However, the sequence feature of them has not been considered in most cases. In addition, data scarcity is still the main obstacle for deep learning strategies, especially for bioactivity datasets. In this study, we propose the convolutional recurrent neural network and transfer learning (CRNNTL) method inspired by the applications of polyphonic sound detection and ECG classification. Our model takes advantage of both convolutional and recurrent neural networks for feature extraction, as well as the data augmentation method. According to QSAR modeling on 27 datasets, CRNNTL can outperform or compete with state-of-art methods in both drug and material properties. In addition, the performances on one isomers-based dataset indicate that its excellent performance results from the improved ability in global feature extraction when the ability of the local one is maintained. Then, the transfer learning results show that CRNNTL can overcome data scarcity when choosing relative source datasets. Finally, the high versatility of our model is shown by using different latent representations as inputs from other types of AEs. The experimental process involved the reaction of Pentane-1,5-diol(cas: 111-29-5).Product Details of 111-29-5
The Article related to crnntl qsar modeling organic drug material discovery, cnn, deep learning, qsar, rnn, molecular autoencoders, transfer learning, Biochemical Methods: Other (Not Covered At Other Subsections) and other aspects.Product Details of 111-29-5
Referemce:
Alcohol – Wikipedia,
Alcohols – Chemistry LibreTexts