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Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models [article]

Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas, Nathan Baker
2017 arXiv   pre-print
Having matched the performance of expert-developed QSAR/QSPR deep learning models, our work demonstrates the plausibility of using deep neural networks to assist in computational chemistry research, where  ...  Inspired by Google's Inception-ResNet deep convolutional neural network (CNN) for image classification, we have developed "Chemception", a deep CNN for the prediction of chemical properties, using just  ...  This deep convolutional neural network, which we term "Chemception", despite being provided the minimal chemical knowledge, achieves a level of performance that is on par with expert-developed QSAR/QSPR  ... 
arXiv:1706.06689v1 fatcat:mlm5bvfgsjdlbdg7lu4l4howqe

CheMixNet: Mixed DNN Architectures for Predicting Chemical Properties using Multiple Molecular Representations [article]

Arindam Paul, Dipendra Jha, Reda Al-Bahrani, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
2018 arXiv   pre-print
SMILES is a linear representation of chemical structures which encodes the connection table, and the stereochemistry of a molecule as a line of text with a grammar structure denoting atoms, bonds, rings  ...  In this work, we present CheMixNet -- a set of neural networks for predicting chemical properties from a mixture of features learned from the two molecular representations -- SMILES as sequences and molecular  ...  Acknowledgments This work was performed under the following financial assistance award 70NANB14H012 from U.S.  ... 
arXiv:1811.08283v2 fatcat:zigst4l7szhf5dzophrqmcqt2m

Artificial Intelligence in Drug Discovery: Applications and Techniques [article]

Jianyuan Deng, Zhibo Yang, Iwao Ojima, Dimitris Samaras, Fusheng Wang
2021 arXiv   pre-print
We also provide a GitHub repository (https://github.com/dengjianyuan/Survey_AI_Drug_Discovery) with the collection of papers and codes, if applicable, as a learning resource, which is regularly updated  ...  Furthermore, to summarize the progress of AI in drug discovery, we present the relevant AI techniques including model architectures and learning paradigms in the papers surveyed.  ...  Acknowledgement This project is partially funded by a Stony Brook University OVPR Seed Grant. The neural networks templates are from Visuals by dair.ai (https://github.com/dair-ai/ml-visuals).  ... 
arXiv:2106.05386v4 fatcat:w2at5y5jyffrxiejsupmwiimhq