Biological networks are powerful resources for the discovery of genes and genetic modules
that drive disease. Fundamental to network analysis is the concept that genes underlying the …

Biological entities are involved in intricate and complex interactions, in which uncovering the
biological information from the network concepts are of great significance. Benefiting from …

We describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC).
Using this dataset, we expand the catalogue of known ACC driver genes to include …

The formation of red blood cells begins with the differentiation of multipotent haematopoietic
progenitors. Reconstructing the steps of this differentiation represents a general challenge in …

Cancers exhibit extensive mutational heterogeneity, and the resulting long-tail phenomenon
complicates the discovery of genes and pathways that are significantly mutated in cancer …

Background Many mutations that contribute to the pathogenesis of acute myeloid leukemia
(AML) are undefined. The relationships between patterns of mutations and epigenetic …

Genetic changes underlying clear cell renal cell carcinoma (ccRCC) include alterations in
genes controlling cellular oxygen sensing (for example, VHL) and the maintenance of …

Determining how somatic copy number alterations (SCNAs) promote cancer is an important
goal. We characterized SCNA patterns in 4,934 cancers from The Cancer Genome Atlas …

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 …

Many forms of cancer have multiple subtypes with different causes and clinical outcomes.
Somatic tumor genome sequences provide a rich new source of data for uncovering these …