Compound inference models are crucial for discovering novel drugs in bioinformatics and
chemo-informatics. These models rely heavily on useful descriptors of chemical compounds …

A novel framework has recently been proposed for designing the molecular structure of
chemical compounds with a desired chemical property, where design of novel drugs is an …

In this paper, we propose a new machine learning method, called adjustive linear
regression, which can be regarded as an ANN on an architecture with an input layer and an …

In this paper, we propose a novel family of descriptors of chemical graphs, named cycle-
configuration (CC), that can be used in the standard" two-layered (2L) model" of mol-infer, a …

A novel framework for designing the molecular structure of chemical compounds with a
desired chemical property has recently been proposed. The framework infers a desired …

Analysis of the activities and properties of chemical compounds is one of the important
applications of intelligent computing. The problem of computational prediction of chemical …