Simple Summary The ongoing advancements in deep learning, notably its use in predicting
cancer survival through genomic data analysis, calls for an up-to-date review. This paper …

Abstract Gene Expression Data is the biological data to extract meaningful hidden
information from the gene dataset. This gene information is used for disease diagnosis …

Background The recent development of high-throughput sequencing has created a large
collection of multi-omics data, which enables researchers to better investigate cancer …

Recent technological advances and international efforts, such as The Cancer Genome Atlas
(TCGA), have made available several pan-cancer datasets encompassing multiple omics …

With rapid development of single-cell multi-modal sequencing technologies, more and more
multi-omics data come into being and provide a unique opportunity for the identification of …

The essential problem of multi-view spectral clustering is to learn a good common
representation by effectively utilizing multi-view information. A popular strategy for improving …

Advances of high throughput experimental methods have led to the availability of more
diverse omic datasets in clinical analysis applications. Different types of omic data reveal …

Breast cancer is a heterogeneous disease and can be divided into several subtypes with
unique prognostic and molecular characteristics. The classification of breast cancer …

Cancer is one of the leading causes of death worldwide, which brings an urgent need for its
effective treatment. However, cancer is highly heterogeneous, meaning that one cancer can …

The remarkable growth of multi-platform genomic profiles has led to the challenge of
multiomics data integration. In this study, we present a novel network-based multiomics …