Highlights•Machine learning techniques (MLTs) are progressing the drug discovery
process.•Conventional MLTs require large data, lack transparency and are not …

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to
quantify the gene expression profile of thousands of single cells simultaneously. Analysis of …

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

A rising amount of research demonstrates that artificial intelligence and machine learning
approaches can provide an essential basis for the drug design and discovery process. Deep …

The evolving field of generative artificial intelligence (GenAI), particularly generative deep
learning, is revolutionizing a host of scientific and technological sectors. One of the pivotal …

The selection of the elements to combine delimits the possible outcomes of synthetic
chemistry because it determines the range of compositions and structures, and thus …

A growing body of evidence currently proposes that deep learning approaches can serve as
an essential cornerstone for the diagnosis and prediction of Alzheimer's disease (AD). In …

A growing body of evidence now suggests that artificial intelligence and machine learning
techniques can serve as an indispensable foundation for the process of drug design and …

In recent years, the application of single-cell transcriptomics and spatial transcriptomics
analysis techniques has become increasingly widespread. Whether dealing with single-cell …

Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells,
which has given us insights into cell–cell communication, cell differentiation, and differential …