The process of constructing and testing models, particularly those that incorporate significant prior knowledge, involves multiple steps that are currently very poorly integrated. We have developed SB-Pipeline to create an effective workflow based on open-source code, public standards and modern software practice.

SB-Pipeline is a multi-faceted software platform that pulls together all of the steps involved in collecting and transforming primary data; constructing, annotating and calibrating models; and distributing and sharing simulations and analyses. SB-Pipeline is primarily concerned with data and model management for the purpose of calibration; in existing modeling tools, calibration is an ancillary rather than a primary activity. Conversely, SB-Pipeline does not recreate existing tools for model simulation. Second, SB-Pipeline implements a robust system for tracking the provenance of data, links between data and models, and the origins of model assumptions in data or the literature. Third, SB-Pipeline is a collection of discrete but interoperable software tools, rather than a single integrated system. SB-Pipeline incorporates standard protocols for import and export of data and thus components can be integrated into external packages.

SBPipeline comprises a number of toolboxes to store and handle data and models in systems biology:

DataRail is an open source MATLAB toolbox for managing, transforming, visualizing, and modeling data, in particular the high-throughput data encountered in Systems Biology.

CellNetOptimizer is a MATLAB toolbox for creating logic-based models of signal transduction networks, and training them agains high-throughput biochemical data.

SbWiki is a wiki-based system which utilizes Semantic Web technologies and a lightweight data entry and cataloging framework to support collaborative management of unstructured and semi-structured Systems Biology data.