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 …

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 …

Multi‐omics usually refers to the crossover application of multiple high‐throughput screening
technologies represented by genomics, transcriptomics, single‐cell transcriptomics …

Motivation In the continuously expanding omics era, novel computational and statistical
strategies are needed for data integration and identification of biomarkers and molecular …

These guidelines are a consensus work of a considerable number of members of the
immunology and flow cytometry community. They provide the theory and key practical …

With the rapid adoption of high-throughput omic approaches to analyze biological samples
such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can …

Recent high throughput experimental methods have been used to collect large biomedical
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …

Gene co-expression networks can be used to associate genes of unknown function with
biological processes, to prioritize candidate disease genes or to discern transcriptional …

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