A knowledge representation meta-model for rule-based modelling of signalling networks

The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes--at least apparently--inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers--each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.Comment: In Proceedings DCM 2015, arXiv:1603.0053

Efficient Groundness Analysis in Prolog

Boolean functions can be used to express the groundness of, and trace grounding dependencies between, program variables in (constraint) logic programs. In this paper, a variety of issues pertaining to the efficient Prolog implementation of groundness analysis are investigated, focusing on the domain of definite Boolean functions, Def. The systematic design of the representation of an abstract domain is discussed in relation to its impact on the algorithmic complexity of the domain operations; the most frequently called operations should be the most lightweight. This methodology is applied to Def, resulting in a new representation, together with new algorithms for its domain operations utilising previously unexploited properties of Def -- for instance, quadratic-time entailment checking. The iteration strategy driving the analysis is also discussed and a simple, but very effective, optimisation of induced magic is described. The analysis can be implemented straightforwardly in Prolog and the use of a non-ground representation results in an efficient, scalable tool which does not require widening to be invoked, even on the largest benchmarks. An extensive experimental evaluation is givenComment: 31 pages To appear in Theory and Practice of Logic Programmin

An investigation of resource-allocation decisions by means of project networks.

This paper investigates the relationship between resource allocation and ES-policies, which are a type of scheduling policies introduced for stochastic scheduling and which can be represented by a directed acyclic graph. We present a formal treatment of resource flows as are presentation of resource-allocation decisions, extending the existing literature. A number of complexity results are established, showing that a number of recently proposed objective functions for evaluating the quality of ES-policies lead to difficult problems. Finally, some reflections are provided on possible effciency enhancements to enumeration algorithms for ES-policies.Complexity; Project scheduling; Resource allocation; Resource constraints;

Stability and resource allocation in project planning.

The majority of resource-constrained project scheduling efforts assumes perfect information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule is executed. In reality, project activities are subject to considerable uncertainty, which generally leads to numerous schedule disruptions. In this paper, we present a resource allocation model that protects a given baseline schedule against activity duration variability. A branch-and-bound algorithm is developed that solves the proposed resource allocation problem. We report on computational results obtained on a set of benchmark problems.Constraint satisfaction; Information; Model; Planning; Problems; Project management; Project planning; Project scheduling; Resource allocati; Scheduling; Stability; Uncertainty; Variability;

Domain-specific languages in Prolog for declarative expert knowledge in rules and ontologies

Declarative if–then rules have proven very useful in many applications of expert sys- tems. They can be managed in deductive databases and evaluated using the well-known forward-chaining approach. For domain-experts, however, the syntax of rules becomes complicated quickly, and already many different knowledge representation formalisms ex- ist. Expert knowledge is often acquired in story form using interviews. In this paper, we discuss its representation by defining domain-specific languages (Dsls) for declarative ex- pert rules. They can be embedded in Prolog systems in internal Dsls using term expan- sion and as external Dsls using definite clause grammars and quasi-quotations – for more sophisticated syntaxes. Based on the declarative rules and the integration with the Prolog-based deductive database system DDbase, multiple rules acquired in practical case studies can be combined, compared, graphically analysed by domain-experts, and evaluated, resulting in an extensi- ble system for expert knowledge. As a result, the actual modeling Dsl becomes executable; the declarative forward-chaining evaluation of deductive databases can be understood by the domain experts. Our Dsl for rules can be further improved by integrating ontologies and rule annotations

Policy-Driven Framework for Static Identification and Verification of Component Dependencies

Software maintenance is considered to be among the most difficult, lengthy and costly parts of a software application's life-cycle. Regardless of the nature of the software application and the software engineering efforts to reduce component coupling to minimum, dependencies between software components in applications will always exist and initiate software maintenance operations as they tend to threaten the "health" of the software system during the evolution of particular components. The situation is more serious with modern technologies and development paradigms, such as Service Oriented Architecture Systems and Cloud Computing that introduce larger software systems that consist of a substantial number of components which demonstrate numerous types of dependencies with each other. This work proposes a reference architecture and a corresponding software framework that can be used to model the dependencies between components in software systems and can support the verification of a set of policies that are derived from system dependencies and are relative to the software maintenance operations being applied. Dependency modelling is performed using configuration information from the system, as well as information harvested from component interface descriptions. The proposed approach has been applied to a medium scale SOA system, namely the SCA Travel Sample from Apache Software Foundation, and has been evaluated for performance in a configuration specification related to a simulated SOA system consisting to up to a thousand web services offered in a few hundred components