AIMC Journal:
Molecules (Basel, Switzerland)

Showing 151 to 160 of 243 articles

Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.

Molecules (Basel, Switzerland) Dec 13, 2020
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...
Blood-Brain Barrier Animals Organic Chemicals Neural Networks, Computer Algorithms Models, Biological Biological Transport Permeability Molecular Structure Workflow Humans
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Machine Learning Methods in Drug Discovery.

Molecules (Basel, Switzerland) Nov 12, 2020
The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been use...
Algorithms Databases, Factual Reproducibility of Results Machine Learning Software Computational Biology Support Vector Machine Bayes Theorem Drug Discovery Deep Learning Humans Internet Monte Carlo Method
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Concentration-Emission Matrix (CEM) Spectroscopy Combined with GA-SVM: An Analytical Method to Recognize Oil Species in Marine.

Molecules (Basel, Switzerland) Nov 4, 2020
The establishment and development of a set of methods of oil accurate recognition in a different environment are of great significance to the effective management of oil spill pollution. In this work, the concentration-emission matrix (CEM) is formed...
Principal Component Analysis Spectroscopy, Near-Infrared Petroleum Support Vector Machine Petroleum Pollution Seawater Water Pollutants, Chemical
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Authentication and Provenance of Walnut Combining Fourier Transform Mid-Infrared Spectroscopy with Machine Learning Algorithms.

Molecules (Basel, Switzerland) Oct 28, 2020
Different varieties and geographical origins of walnut usually lead to different nutritional values, contributing to a big difference in the final price. The conventional analytical techniques have some unavoidable limitations, e.g., chemical analysi...
Machine Learning Juglans Geography Spectroscopy, Fourier Transform Infrared Food Quality
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Fuzzy Divisive Hierarchical Associative-Clustering Applied to Different Varieties of White Wines According to Their Multi-Elemental Profiles.

Molecules (Basel, Switzerland) Oct 26, 2020
Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data. Therefore, the fuzzy divisi...
Fuzzy Logic Food Analysis Cluster Analysis Wine
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A Machine Learning Approach in Analyzing Bioaccumulation of Heavy Metals in Turbot Tissues.

Molecules (Basel, Switzerland) Oct 14, 2020
Metals are considered to be one of the most hazardous substances due to their potential for accumulation, magnification, persistence, and wide distribution in water, sediments, and aquatic organisms. Demersal fish species, such as turbot (), are acce...
Metals, Heavy Machine Learning Flatfishes Animals Nonlinear Dynamics Environmental Biomarkers Europe Water Pollutants, Chemical Linear Models Muscle, Skeletal Bioaccumulation Liver Environmental Monitoring
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Cryostructuring of Polymeric Systems : Application of Deep Neural Networks for the Classification of Structural Features Peculiar to Macroporous Poly(vinyl alcohol) Cryogels Prepared without and with the Additives of Chaotropes or Kosmotropes.

Molecules (Basel, Switzerland) Sep 29, 2020
Macroporous poly(vinyl alcohol) cryogels (PVACGs) are physical gels formed via cryogenic processing of polymer solutions. The properties of PVACGs depend on many factors: the characteristics and concentration of PVA, the absence or presence of foreig...
Elastic Modulus Neural Networks, Computer Cryogels Hot Temperature Porosity Polymers Polyvinyl Alcohol Freezing
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LncMirNet: Predicting LncRNA-miRNA Interaction Based on Deep Learning of Ribonucleic Acid Sequences.

Molecules (Basel, Switzerland) Sep 23, 2020
Long non-coding RNA (LncRNA) and microRNA (miRNA) are both non-coding RNAs that play significant regulatory roles in many life processes. There is cumulating evidence showing that the interaction patterns between lncRNAs and miRNAs are highly related...
Deep Learning RNA, Messenger Time Factors Sequence Analysis, RNA Computational Biology RNA, Long Noncoding
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A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers.

Molecules (Basel, Switzerland) Sep 23, 2020
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein-protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and ge...
Protein Structure, Quaternary Proteins Protein Multimerization Computational Biology Support Vector Machine
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Computational Method for Quantitative Comparison of Activity Landscapes on the Basis of Image Data.

Molecules (Basel, Switzerland) Aug 29, 2020
Activity landscape (AL) models are used for visualizing and interpreting structure-activity relationships (SARs) in compound datasets. Therefore, ALs are designed to present chemical similarity and compound potency information in context. Different t...
Models, Molecular Drug Discovery Machine Learning Structure-Activity Relationship Drug Design
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