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 …

In recent years, high-throughput sequencing technologies provide unprecedented
opportunity to depict cancer samples at multiple molecular levels. The integration and …

With biotechnological advancements, innovative omics technologies are constantly
emerging that have enabled researchers to access multi-layer information from the genome …

Data analytics is routinely used to support biomedical research in all areas, with particular
focus on the most relevant clinical conditions, such as cancer. Bioinformatics approaches, in …

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

Oncogenesis and cancer can arise as a consequence of a wide range of genomic
aberrations including mutations, copy number alterations, expression changes and …

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

While cost-effective high-throughput technologies provide an increasing amount of data, the
analyses of single layers of data seldom provide causal relations. Multi-omics data …

Multi-omics approaches are novel frameworks that integrate multiple omics datasets
generated from the same patients to better understand the molecular and clinical features of …

In-depth modeling of the complex interplay among multiple omics data measured from
cancer cell lines or patient tumors is providing new opportunities toward identification of …