Rare diseases affect 30 million people in the USA and more than 300–400 million
worldwide, often causing chronic illness, disability, and premature death. Traditional …

The world has witnessed a steady rise in both non-infectious and infectious chronic
diseases, prompting a cross-disciplinary approach to understand and treating disease …

Generative pretrained models have achieved remarkable success in various domains such
as language and computer vision. Specifically, the combination of large-scale diverse …

The rapid developments of high‐throughput sequencing technology in the last decade
allowed the emergence of multiomics analyses. Analytic platforms for high‐throughput omics …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

A molecular classification of diseases that accurately reflects clinical behaviour lays the
foundation of precision medicine. The development of in silico classifiers coupled with …

High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

Multi-omics, variously called integrated omics, pan-omics, and trans-omics, aims to combine
two or more omics data sets to aid in data analysis, visualization and interpretation to …

An individualized innovative disease management is of great importance for people with
multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional …

Multi-omics data analysis is an important aspect of cancer molecular biology studies and
has led to ground-breaking discoveries. Many efforts have been made to develop machine …