For several industries, the traditional manufacturing processes are time-consuming and
uneconomical due to the absence of the right tool to produce the products. In a couple of …

The nature of manufacturing systems faces ever more complex, dynamic and at times even
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …

Background In recent years, research in artificial neural networks has resurged, now under
the deep-learning umbrella, and grown extremely popular. Recently reported success of DL …

We show that the support vector machine (SVM) classification algorithm, a recent
development from the machine learning community, proves its potential for structure–activity …

Multiple contact miscible floods such as injection of relatively inexpensive gases into oil
reservoirs are considered as well-established enhanced oil recovery (EOR) techniques for …

This review is dedicated to a survey on molecular similarity and diversity. Key findings
reported in recent investigations are selectively highlighted and summarized. Even if this …

Emperial methods for building predictive models of the relationships between molecular
stucture and useful properties are becoming increasingly importment. This has arisen …

An unsupervised learning method is proposed for variable selection and its performance
assessed using three typical QSAR data sets. The aims of this procedure are to generate a …

Chemical space has become a key concept in drug discovery. The continued growth in the
number of molecules available raises the question regarding how many compounds may …

Modern strategies of computer-aided drug design (CADD) are reviewed. The task of CADD
in the pipeline of drug discovery is accelerating of finding the new lead compounds and their …