Databases and tools for constructing signal transduction networks in cancer

Abstract

Traditionally, biologists have devoted their careers to studyingindividual biological entities of their own interest, partly dueto lack of available data regarding that entity. Large, highthroughputdata, too complex for conventional processingmethods (i.e., "big data"), has accumulated in cancer biology,which is freely available in public data repositories. Suchchallenges urge biologists to inspect their biological entities ofinterest using novel approaches, firstly including repositorydata retrieval. Essentially, these revolutionary changes demandnew interpretations of huge datasets at a systems-level, by socalled "systems biology". One of the representative applicationsof systems biology is to generate a biological networkfrom high-throughput big data, providing a global map ofmolecular events associated with specific phenotype changes.In this review, we introduce the repositories of cancer big dataand cutting-edge systems biology tools for network generation,and improved identification of therapeutic targets.