Recent genome sequencing studies have shown that the somatic mutations that drive
cancer development are distributed across a large number of genes. This mutational …

Next-generation DNA sequencing technologies are enabling genome-wide measurements
of somatic mutations in large numbers of cancer patients. A major challenge in the …

Cancer is a heterogeneous disease with different combinations of genetic alterations
driving its development in different individuals. We introduce CoMEt, an algorithm to identify …

The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to
identify somatic variants across thousands of tumours. Here we present data and analytical …

Abstract Characterization of the prostate cancer transcriptome and genome has identified
chromosomal rearrangements and copy number gains and losses, including ETS gene family …

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

High-throughput DNA sequencing is revolutionizing the study of cancer and enabling the
measurement of the somatic mutations that drive cancer development. However, the resulting …

In the past few years, graph neural networks (GNNs) have become the de facto model of choice
for graph classification. While, from the theoretical viewpoint, most GNNs can operate on …

A major goal of cancer sequencing projects is to identify genetic alterations that determine
clinical phenotypes, such as survival time or drug response. Somatic mutations in cancer are …

Sensor-based human activity recognition (HAR) requires to predict the action of a person
based on sensor-generated time series data. HAR has attracted major interest in the past few …