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

Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

Multi‐omics studies promise the improved characterization of biological processes across
molecular layers. However, methods for the unsupervised integration of the resulting …

New technologies have enabled the investigation of biology and human health at an
unprecedented scale and in multiple dimensions. These dimensions include a myriad of …

Multi-omics data integration is one of the major challenges in the era of precision medicine.
Considerable work has been done with the advent of high-throughput studies, which have …

Biological networks are powerful resources for the discovery of genes and genetic modules
that drive disease. Fundamental to network analysis is the concept that genes underlying the …

The field of machine learning, which aims to develop computer algorithms that improve with
experience, holds promise to enable computers to assist humans in the analysis of large …

Recent technological advances have expanded the breadth of available omic data, from
whole-genome sequencing data, to extensive transcriptomic, methylomic and metabolomic …

In recent years, several methods have been proposed to combine multiple kernels instead of
using a single one. These different kernels may correspond to using different notions of …