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Quantitative Structure-Activity Relationship

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VISAR: an interactive tool for dissecting chemical features learned by deep neural network QSAR models.

Bioinformatics (Oxford, England)
SUMMARY: Although many quantitative structure-activity relationship (QSAR) models are trained and evaluated for their predictive merits, understanding what models have been learning is of critical importance. However, the interpretation and visualiza...

Artificial Neural Networks in Computer-Aided Drug Design: An Overview of Recent Advances.

Advances in experimental medicine and biology
Computer-aided drug design (CADD) is the framework in which the huge amount of data accumulated by high-throughput experimental methods used in drug design is quantitatively studied. Its objectives include pattern recognition, biomarker identificatio...

[AI-based QSAR Modeling for Prediction of Active Compounds in MIE/AOP].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Toxicity testing is critical for new drug and chemical development process. A clinical study, experimental animal models, and in vitro study are performed to evaluate the safety of a new drug. The limitations of these methods include extensive time f...

Positive Predictive Value Surfaces as a Complementary Tool to Assess the Performance of Virtual Screening Methods.

Mini reviews in medicinal chemistry
BACKGROUND: Since their introduction in the virtual screening field, Receiver Operating Characteristic (ROC) curve-derived metrics have been widely used for benchmarking of computational methods and algorithms intended for virtual screening applicati...

FP2VEC: a new molecular featurizer for learning molecular properties.

Bioinformatics (Oxford, England)
MOTIVATION: One of the most successful methods for predicting the properties of chemical compounds is the quantitative structure-activity relationship (QSAR) methods. The prediction accuracy of QSAR models has recently been greatly improved by employ...

Machine learning-based chemical binding similarity using evolutionary relationships of target genes.

Nucleic acids research
Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional ac...

Inhibition activity prediction for a dataset of candidates' drug by combining fuzzy logic with MLR/ANN QSAR models.

Chemical biology & drug design
A hybrid of artificial intelligence simple and low computational cost QSAR was used. Approximately 90 pyridinylimidazole-based drug candidates with a range of potencies against p38R MAP kinase were investigated. To obtain more flexibility and effecti...

Filter feature selectors in the development of binary QSAR models.

SAR and QSAR in environmental research
The application of machine learning methods to the construction of quantitative structure-activity relationship models is a complex computational problem in which dimensionality reduction of the representation of the molecular structure plays a funda...