Interactive exploration of integrated biological datasets using context-sensitive workflows.

ABSTRACT: Network inference utilizes experimental high-throughput data for the reconstruction of molecular interaction networks where new relationships between the network entities can be predicted. Despite the increasing amount of experimental data, the parameters of each modeling technique cannot be optimized based on the experimental data alone, but needs to be qualitatively assessed if the components of the resulting network describe the experimental setting. Candidate list prioritization and validation builds upon data integration and data visualization. The application of tools supporting this procedure is limited to the exploration of smaller information networks because the display and interpretation of large amounts of information is challenging regarding the computational effort and the us

SUBMITTER: Horn F 

PROVIDER: S-EPMC3929842 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature