UNLABELLED: Class-responsibility-collaboration (CRC) cards have been used extensively in the software industry for defining complex object-oriented software requirements. We have adapted this tool to capture information about biological components, collaborators and responsibilities within these collaborations, which is not captured by current annotation tools. CRC cards should provide a common ground that will facilitate communication between biologist and computer scientists. AVAILABILITY: A CRC card template, XML representation and XML schema are freely available at http://people.musc.edu/~zhengw/CRCCard/CRC_Card_Index.html SUPPLEMENTARY INFORMATION: Supplemental Figures 1-4.

MOTIVATION: The importance of studying biology at the system level has been well recognized, yet there is no well-defined process or consistent methodology to integrate and represent biological information at this level. To overcome this hurdle, a blending of disciplines such as computer science and biology is necessary. RESULTS: By applying an adapted, sequential software engineering process, a complex biological system (severe acquired respiratory syndrome-coronavirus viral infection) has been reverse-engineered and represented as an object-oriented software system. The scalability of this object-oriented software engineering approach indicates that we can apply this technology for the integration of large complex biological systems. AVAILABILITY: A navigable web-based version of the system is freely available at http://people.musc.edu/~zhengw/SARS/Software-Process.htm

BACKGROUND: To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO) has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. RESULTS: Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta) receptor complex assembly" (GO:0007181). CONCLUSION: We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.