Figure 1: Synapse platform architecture.
From: Developing predictive molecular maps of human disease through community-based modeling
Synapse uses a set of web services to provide access to the data repository, which comprises a federated collection of curated, adjusted and analyzed datasets, models and code. Synapse may also reference restricted data stored in external databases, such as dbGAP or The Cancer Genome Atlas (TCGA). All resources managed by Synapse can be referenced as objects using a URL according to linked data principles. This approach allows for the storage of data and metadata using persistence mechanisms that are appropriate for each data modality while abstracting clients away from the details of how data and services are obtained. Integration with ontology services and support for a rich query language occurs on the Synapse backend, allowing multiple clients (for example, R and the web client) to run similar queries across hosted data. Versioning of data, workflows and tools allows for the documentation of details on how individual models were generated, and enables these models to be reproduced. Storage of the data repository and services in the cloud allows for scalability, access and the potential to use high performance computing facilities directly from Synapse.
