Ruminant production systems face significant challenges currently, driven by heightened
awareness of their negative environmental impact and the rapidly rising global population …

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

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 …

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

Background Methods for the integrative analysis of multi-omics data are required to draw a
more complete and accurate picture of the dynamics of molecular systems. The complexity …

Computational integrative analysis has become a significant approach in the data-driven
exploration of biological problems. Many integration methods for cancer subtyping have …

In vitro human cell line models have been widely used for cancer pharmacogenomic studies
to predict clinical response, to help generate pharmacogenomic hypothesis for further …

With the recent developments in the field of multi-omics integration, the interest in factors
such as data preprocessing, choice of the integration method and the number of different …

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in
even individual malignant cells. Epigenetic changes are critical mediators of these functional …

Background Classifying breast cancer subtypes is crucial for clinical diagnosis and
treatment. However, the early symptoms of breast cancer may not be apparent. Rapid …