出版社：European Association of Software Science and Technology (EASST)
摘要：High-level graph data structures have gained favour in representing biological knowledge in a computationally executable form, but the information contained therein must remain accessible to all users no matter their background. Bidirectional graph transformations may be used to synchronise and maintain the consistency of these graph data structures as they evolve through the process of creating and refining a bio-model knowledge base. We outline a bidirectional collaboration framework by which users with vastly differing backgrounds may contribute to the development and evolution of such a knowledge base, and examine a simple example to illustrate its merits. We also identify avenues for further research necessary to refine the framework. No prior biological knowledge is assumed.
