004 Datenverarbeitung; Informatik
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We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.
Aspect-oriented middleware is a promising technology for the realisation of dynamic reconfiguration in heterogeneous distributed systems. However, like other dynamic reconfiguration approaches, AO-middleware-based reconfiguration requires that the consistency of the system is maintained across reconfigurations. AO-middleware-based reconfiguration is an ongoing research topic and several consistency approaches have been proposed. However, most of these approaches tend to be targeted at specific contexts, whereas for distributed systems it is crucial to cover a wide range of operating conditions. In this paper we propose an approach that offers distributed, dynamic reconfiguration in a consistent manner, and features a flexible framework-based consistency management approach to cover a wide range of operating conditions. We evaluate our approach by investigating the configurability and transparency of our approach and also quantify the performance overheads of the associated consistency mechanisms.