Application of Symmetry Functions to Large Chemical Spaces Using Convolutional Neural Network.

07:00 EST 13th February 2020 | BioPortfolio

Summary of "Application of Symmetry Functions to Large Chemical Spaces Using Convolutional Neural Network."

The use of machine learning in chemistry is on the rise for the prediction of chemical properties. The input feature representation or descriptor in these applications is an important factor that affects the accuracy as well as the extent of the explored chemical space. Here, we present the Periodic Table Tensor descriptor that combines features from Behler-Parrinello's symmetry functions and a Periodic Table Representation. Using our descriptor and a convolutional neural network model, we achieved 2.2 kcal/mol and 94 meV/atom Mean Absolute Error (MAE) for the prediction of the atomization energy of organic molecules in the QM9 dataset and the formation energy of materials from Materials Project dataset, respectively. We also show that structures optimized with Force Field can be used as input to predict the atomization energies of molecules at DFT level. Our approach extends the application of Behler-Parrinello's symmetry functions without a limitation on the number of elements, which is highly promising for universal property calculators in large chemical spaces.


Journal Details

This article was published in the following journal.

Name: Journal of chemical information and modeling
ISSN: 1549-960X


DeepDyve research library

PubMed Articles [21181 Associated PubMed Articles listed on BioPortfolio]

A brief comparison between experimental and computationally-generated ensembles of RNA dinucleotides.

The computational modeling of RNA and its interactions is of crucial importance for the understanding of the wide variety of biological functions it performs. Among these approaches, several coarse-gr...

Efficient Treatment of Large Active Spaces through Multi-GPU Parallel Implementation of Direct Configuration Interaction.

We have extended our graphical processing unit (GPU) accelerated direct configuration interaction program to multiple devices, reducing iteration times for configuration spaces of 165 million determin...

Automatic Symmetry Detection From Brain MRI Based on a 2-Channel Convolutional Neural Network.

Symmetry detection is a method to extract the ideal mid-sagittal plane (MSP) from brain magnetic resonance (MR) images, which can significantly improve the diagnostic accuracy of brain diseases. In th...

Theory of deep convolutional neural networks: Downsampling.

Establishing a solid theoretical foundation for structured deep neural networks is greatly desired due to the successful applications of deep learning in various practical domains. This paper aims at ...

ImageDataExtractor: A Tool to Extract and Quantify Data from Microscopy Images.

The rise of data science is leading to new paradigms in data-driven materials discovery. This carries an essential notion that large data sources containing chemical structure and property information...

Clinical Trials [6702 Associated Clinical Trials listed on BioPortfolio]

Efficacy of Laser Application in Dental Bleaching

Objective: To establish the efficacy of laser application with chemical treatment in dental bleaching compared to chemical treatment alone. Methods: The investigators conducted a randomiz...

A New Method of Muscle Strength Testing Using a Quantitative Ultrasonic Technique and a Convolutional Neural Network

In addition to muscle thickness and average echo intensity, this study aimed to use quantitative ultrasonic technology to increase the number of related parameters of power Doppler ultraso...

Renal Cancer Detection Using Convolutional Neural Networks

We aim to experiment and implement various deep learning architectures in order to achieve human-level accuracy in Computer-aided diagnosis (CAD) systems. In particular, we are interested ...

Comparison of the Effects of Controlled Schroth Exercise and Home Exercise Programs

The aim of this study is to compare the effects of Schroth 3D exercise method on home symmetry, trunk topography, scapula symmetry, pelvic symmetry, health related quality of life and cosm...

Improving Physical Activity and Gait Symmetry After Total Knee Arthroplasty

The purpose of this pilot study is to examine the effectiveness of the Physical Activity and Symmetry (PAS) program, compared to an attention (ATT)control group, for patients with post-tot...

Medical and Biotech [MESH] Definitions

A class of unsegmented helminths with fundamental bilateral symmetry and secondary triradiate symmetry of the oral and esophageal structures. Many species are parasites.

An application that must be submitted to a regulatory agency (the FDA in the United States) before a drug can be studied in humans. This application includes results of previous experiments; how, where, and by whom the new studies will be conducted; the chemical structure of the compound; how it is thought to work in the body; any toxic effects found in animal studies; and how the compound is manufactured. (From the "New Medicines in Development" Series produced by the Pharmaceutical Manufacturers Association and published irregularly.)

Large cytoplasmic ribonucleoprotein particles that have an eight-fold symmetry with a central pore and petal-like structure giving the appearance of an octagonal dome. (The Dictionary of Cell Biology, Lackie and Dow, 2nd ed.)

The formation of a solid in a solution as a result of a chemical reaction or the aggregation of soluble substances into complexes large enough to fall out of solution.

Application of principles and practices of engineering science to the transformation, design, and manufacture of substances on an industrial scale.

Quick Search

DeepDyve research library

Searches Linking to this Article