Artificial Intelligence (AI) has revolutionized various domains, including education and
research. Natural language processing (NLP) techniques and large language models …

Molecular docking is an established in silico structure-based method widely used in drug
discovery. Docking enables the identification of novel compounds of therapeutic interest …

We assess costs and efficiency of state-of-the-art high-performance cloud computing and
compare the results to traditional on-premises compute clusters. Our use case is atomistic …

The explosion of the data both in the biomedical research and in the healthcare systems
demands urgent solutions. In particular, the research in omics sciences is moving from a …

Introduction: Artificial intelligence (AI) and machine learning (ML) are increasingly used in
many aspects of drug discovery. Larger data sizes and methods such as Deep Neural …

At present, every nation is focused on meeting sustainable development goals (SDGs) by
2030 for social, economic, and environmental sustainability. Automation of drug discovery …

High throughput platforms available in clinical settings or in research laboratories, such as
magnetic resonance imaging, microarray, mass spectrometry and next-generation …

Metagenomic studies are becoming increasingly widespread, yielding important insights
into microbial communities covering diverse environments from terrestrial to aquatic …

The amount of available data is continuously growing. This phenomenon promotes a new
concept, named big data. The highlight technologies related to big data are cloud computing …

Introduction: The complexity in the drug discovery pipeline, in combination with the
exponential growth of experimental and computational data, the technological …