There have been numerous advances in the development of computational and statistical
methods and applications of big data and artificial intelligence (AI) techniques for computer …

Analysis of the literature involving computational modeling of diseases and drug design with
the aid of experimental spectroscopic techniques reveals that this specific combination of …

Explainability is essential for users to effectively understand, trust, and manage powerful
artificial intelligence solutions. Decision trees are one of the pioneer explanaible artificial …

IL28B single nucleotide polymorphism (rs12979860) is an etiology-independent predictor of
hepatitis C virus (HCV)-related hepatic fibrosis. Data mining is a method of predictive …

Decision-tree induction algorithms are widely used in machine learning applications in
which the goal is to extract knowledge from data and present it in a graphically intuitive way …

Molecular dynamics simulations of protein receptors have become an attractive tool for
rational drug discovery. However, the high computational cost of employing molecular …

We report here the discovery, synthesis and screening results of a series of 3-(9H-fluoren-9-
yl) pyrrolidine-2, 5-dione derivatives as a novel class of potent inhibitors of Mycobacterium …

Disease phenotypes are generally caused by the failure of gene modules which often have
similar biological roles. Through the study of biological networks, it is possible to identify the …

The chestnut gall wasp (CGW), Dryocosmus kuriphilus, an invasive pest native to China, has
caused severe yield and economic losses to chestnut production in Europe since its arrival …

Decision-tree induction algorithms are widely used in knowledge discovery and data mining,
specially in scenarios where model comprehensibility is desired. A variation of the traditional …