Background Multi-omics experimental approaches are becoming common practice in
biological and medical sciences underlining the need to design new integrative techniques …

To study complex biological processes holistically, it is imperative to take an integrative
approach that combines multi-omics data to highlight the interrelationships of the involved …

Background Studies on multiple modalities of omics data such as transcriptomics, genomics
and proteomics are growing in popularity, since they allow us to investigate complex …

Recent advances in high-throughput technologies have enabled the profiling of multiple
layers of a biological system, including DNA sequence data (genomics), RNA expression …

The advent of high throughput technologies has led to a wealth of publicly available 'omics
data coming from different sources, such as transcriptomics, proteomics, metabolomics …

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 …

The number of studies that collect and publish large-scale multiomics data is rapidly
increasing. So far, we have not realized the full potential of the biological insights that can be …

Motivation: With the availability of many 'omics' data, such as transcriptomics, proteomics or
metabolomics, the integrative or joint analysis of multiple datasets from different technology …

Data analysis and interpretation remain a critical bottleneck in current multi-omics studies.
Here, we introduce OmicsAnalyst, a user-friendly, web-based platform that allows users to …

Integrative omics is a central component of most systems biology studies. Computational
methods are required for extracting meaningful relationships across different omics layers …