AIMC Journal:
Molecules (Basel, Switzerland)

Showing 181 to 190 of 243 articles

Prediction Model of Aryl Hydrocarbon Receptor Activation by a Novel QSAR Approach, DeepSnap-Deep Learning.

Molecules (Basel, Switzerland) Mar 13, 2020
The aryl hydrocarbon receptor (AhR) is a ligand-dependent transcription factor that senses environmental exogenous and endogenous ligands or xenobiotic chemicals. In particular, exposure of the liver to environmental metabolism-disrupting chemicals c...
Animals Deep Learning Principal Component Analysis Models, Molecular Quantitative Structure-Activity Relationship Rats Receptors, Aryl Hydrocarbon Cell Line, Tumor ROC Curve
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Ionic Liquid-Based Ultrasonic-Assisted Extraction Coupled with HPLC and Artificial Neural Network Analysis for .

Molecules (Basel, Switzerland) Mar 13, 2020
is widely used in traditional Chinese medicine (TCM). Ganoderic acid A and D are the main bioactive components with anticancer effects in . To obtain the maximum content of two compounds from , a novel extraction method, an ionic liquid-based ultras...
Chromatography, High Pressure Liquid Ionic Liquids Solvents Time Factors Rotation Reishi Solutions Anions Ultrasonics Reference Standards Neural Networks, Computer Reproducibility of Results
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Hepatotoxicity Modeling Using Counter-Propagation Artificial Neural Networks: Handling an Imbalanced Classification Problem.

Molecules (Basel, Switzerland) Jan 23, 2020
Drug-induced liver injury is a major concern in the drug development process. Expensive and time-consuming and studies do not reflect the complexity of the phenomenon. Complementary to wet lab methods are approaches, which present a cost-efficient...
Liver Drug-Related Side Effects and Adverse Reactions Databases, Chemical Algorithms Computer Simulation Databases, Pharmaceutical Quantitative Structure-Activity Relationship Chemical and Drug Induced Liver Injury Neural Networks, Computer
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Multiple Compounds Recognition from The Tandem Mass Spectral Data Using Convolutional Neural Network.

Molecules (Basel, Switzerland) Dec 15, 2019
Mixtures analysis can provide more information than individual components. It is important to detect the different compounds in the real complex samples. However, mixtures are often disturbed by impurities and noise to influence the accuracy. Purific...
Neural Networks, Computer Algorithms Humans ROC Curve Reproducibility of Results Support Vector Machine Drug Discovery Tandem Mass Spectrometry
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Identification of Similar Chinese Congou Black Teas Using an Electronic Tongue Combined with Pattern Recognition.

Molecules (Basel, Switzerland) Dec 12, 2019
It is very difficult for humans to distinguish between two kinds of black tea obtained with similar processing technology. In this paper, an electronic tongue was used to discriminate samples of seven different grades of two types of Chinese Congou b...
Electronic Nose Humans Neural Networks, Computer Camellia sinensis Tea Support Vector Machine
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A Machine Learning-Based Raman Spectroscopic Assay for the Identification of and Related Species.

Molecules (Basel, Switzerland) Dec 10, 2019
, the causative agent of glanders, and , the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and similar clinical symptoms in ...
Cluster Analysis Workflow Burkholderia mallei Bacterial Typing Techniques Machine Learning Spectrum Analysis, Raman Humans
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Identifying Cancer-Specific circRNA-RBP Binding Sites Based on Deep Learning.

Molecules (Basel, Switzerland) Nov 7, 2019
Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs...
RNA, Neoplasm RNA, Circular Binding Sites Sequence Analysis, Protein Databases, Protein Neoplasm Proteins Neoplasms Humans Deep Learning RNA-Binding Proteins
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Toxicity Prediction Method Based on Multi-Channel Convolutional Neural Network.

Molecules (Basel, Switzerland) Sep 17, 2019
Molecular toxicity prediction is one of the key studies in drug design. In this paper, a deep learning network based on a two-dimension grid of molecules is proposed to predict toxicity. At first, the van der Waals force and hydrogen bond were calcul...
Deep Learning Data Interpretation, Statistical Neural Networks, Computer Molecular Structure Quantitative Structure-Activity Relationship Algorithms
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Rapid Identification of Rainbow Trout Adulteration in Atlantic Salmon by Raman Spectroscopy Combined with Machine Learning.

Molecules (Basel, Switzerland) Aug 6, 2019
This study intends to evaluate the utilization potential of the combined Raman spectroscopy and machine learning approach to quickly identify the rainbow trout adulteration in Atlantic salmon. The adulterated samples contained various concentrations ...
Salmo salar Spectrum Analysis, Raman Machine Learning Oncorhynchus mykiss Adipose Tissue Animals
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Multi-Level Comparison of Machine Learning Classifiers and Their Performance Metrics.

Molecules (Basel, Switzerland) Aug 1, 2019
Machine learning classification algorithms are widely used for the prediction and classification of the different properties of molecules such as toxicity or biological activity. the prediction of toxic vs. non-toxic molecules is important due to tes...
Algorithms Benchmarking Machine Learning
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