Journal of chemical information and modeling
Dec 4, 2018
The specific surface area (SSA) of ABO-type perovskite is one of the important properties associated with photocatalytic ability. In this work, data mining methods were used to explore the relationship between the SSA (in the range of 1-60 m g) of pe...
Despite the increasing volume of available data, the proportion of experimentally measured data remains small compared to the virtual chemical space of possible chemical structures. Therefore, there is a strong interest in simultaneously predicting d...
We present two approaches for the computation of hydrogen bond acceptor strengths, one by machine-learning and one by a composite quantum-mechanical protocol, both based on the well-established pK scale and dataset. The QM calculations after a necess...
Journal of chemical information and modeling
Oct 31, 2018
To achieve simultaneous data visualization and clustering, the method of sparse generative topographic mapping (SGTM) is developed by modifying the conventional GTM algorithm. While the weight of each grid point is constant in the original GTM, it be...
Liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) is a major analytical technique used for nontargeted identification of metabolites in biological fluids. Typically, in LC-ESI-MS/MS based database assi...
The metabolism of xenobiotics by humans and other organisms is a complex process involving numerous enzymes that catalyze phase I (functionalization) and phase II (conjugation) reactions. Herein we introduce MetScore, a machine learning model that ca...
A key consideration at the screening stages of drug discovery is in vitro metabolic stability, often measured in human liver microsomes. Computational prediction models can be built using a large quantity of experimental data available from public da...
The blood-brain barrier (BBB) as a part of absorption protects the central nervous system by separating the brain tissue from the bloodstream. In recent years, BBB permeability has become a critical issue in chemical ADMET prediction, but almost all ...
IEEE/ACM transactions on computational biology and bioinformatics
Aug 7, 2018
Chemical-chemical interaction (CCI) plays a major role in predicting candidate drugs, toxicities, therapeutic effects, and biological functions. CCI is typically inferred from a variety of information; however, CCI has yet not been predicted using a ...
Journal of chemical information and modeling
Jun 27, 2018
Machine learning (ML) algorithms are gaining importance in the processing of chemical information and modeling of chemical reactivity problems. In this work, we have developed a perturbation-theory and machine learning (PTML) model combining perturba...
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