Over the last decade, increasing interest has been attracted towards the application of
artificial intelligence (AI) technology for analyzing and interpreting the biological or genetic …

In cancer, one of the main barriers to effective chemotherapy is inefficient drug delivery. The
delivery of drugs to solid tumors involves various biochemical, biophysical, and mechanical …

Deep learning rapidly promotes many fields with successful stories in natural language
processing. An architecture of deep neural network (DNN) combining tree‐structured long …

We present a new descriptor named signature based on extended valence sequence. The
signature of an atom is a canonical representation of the atom's environment up to a …

The literature describing neural network modelling to predict physicochemical properties of
organic compounds from the molecular structure is reviewed from the perspective of …

A machine learning-quantitative structure property relationship (ML-QSPR) method is
proposed to predict 15 fuel physicochemical properties of 23 fuel types. QSPR-UOB 3.0 …

Boiling point, vapor pressure, and melting point are important physicochemical properties in
the modeling of the distribution and fate of chemicals in the environment. However, such …

The concept of signature as a molecular descriptor is introduced and various topological
indices used in quantitative structure-activity relationships (QSARs) are expressed as …

We test a new algorithm for the search of an optimal subset of molecular descriptors from a
large set of them. As a practical realistic application we predict the normal boiling points of …

Artificial neural networks (ANNs) technology models the pattern recognition capabilities of
the neural networks of the brain. Similarly to a single neuron in the brain, artificial neuron …