The generation of large-scale biomedical data is creating unprecedented opportunities for
basic and translational science. Typically, the data producers perform initial analyses, but it is …

The detection of somatic mutations from cancer genome sequences is key to understanding
the genetic basis of disease progression, patient survival and response to therapy. …

Remote health assessments that gather real-world data (RWD) outside clinic settings
require a clear understanding of appropriate methods for data collection, quality assessment, …

The Cancer Genome Atlas Pan-Cancer Analysis Working Group collaborated on the Synapse
software platform to share and evolve data, results and methodologies while performing …

Although molecular prognostics in breast cancer are among the most successful examples
of translating genomic analysis to clinical applications, optimal approaches to breast cancer …

The inability to identify the molecular causes of disease has led to a disappointing rate of
development of new medicines. By combining the power of community-based modeling with …

Background The phenotypes of cancer cells are driven in part by somatic structural variants.
Structural variants can initiate tumors, enhance their aggressiveness, and provide unique …

Whole-cell models that explicitly represent all cellular components at the molecular level
have the potential to predict phenotype from genotype. However, even for simple bacteria, …

Cancer is a family of diseases caused by somatic genetic mutations. Fundamental questions
remain about the causes of these mutations and their roles in shaping cellular phenotypes 1…

… 29 Kellen MR and Bassingthwaighte JB. An integrative model of coupled water and solute
exchange in cardiac tissue. Am J Physiol Heart Circ Physiol 285: H1303–H1316, 2003. …