Motivation: High-throughput data is providing a comprehensive view of the molecular
changes in cancer tissues. New technologies allow for the simultaneous genome-wide …

Motivation: A current challenge in understanding cancer processes is to pinpoint which
mutations influence the onset and progression of disease. Toward this goal, we describe a …

Motivation: Identifying altered pathways in an individual is important for understanding
disease mechanisms and for the future application of custom therapeutic decisions. Existing …

Identifying the multiple dysregulated oncoproteins that contribute to tumorigenesis in a given
patient is crucial for developing personalized treatment plans. However, accurate inference …

Most cancer genes remain functionally uncharacterized in the physiological context of
disease development. High-throughput molecular profiling and interaction studies are …

We introduce Pathifier, an algorithm that infers pathway deregulation scores for each tumor
sample on the basis of expression data. This score is determined, in a context-specific …

Pathway-centric approaches are widely used to interpret and contextualize-omics data.
However, databases contain different representations of the same biological pathway, which …

With the advent of high-throughput technologies for measuring genome-wide expression
profiles, a large number of methods have been proposed for discovering diagnostic markers …

Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a
normal cell to a malignancy and ultimately to a metastatic state. Certain genetic …

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 …