With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …

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 …

Graph machine learning (GML) is receiving growing interest within the pharmaceutical and
biotechnology industries for its ability to model biomolecular structures, the functional …

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 …

The application of multiple omics technologies in biomedical cohorts has the potential to
reveal patient-level disease characteristics and individualized response to treatment …

Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the
same drugs or surgical methods in patients with the same tumor may have different curative …

Unmasking the subtleties of the immune system requires both a comprehensive knowledge
base and the ability to interrogate that system with intimate sensitivity. That task, to a …

Through the developments of Omics technologies and dissemination of large-scale
datasets, such as those from The Cancer Genome Atlas, Alzheimer's Disease Neuroimaging …

Cancer is defined as a large group of diseases that is associated with abnormal cell growth,
uncontrollable cell division, and may tend to impinge on other tissues of the body by different …