Refine
Year of publication
- 2015 (24) (remove)
Document Type
- Article (17)
- Doctoral Thesis (4)
- Monograph/Edited Volume (1)
- Part of a Book (1)
- Conference Proceeding (1)
Language
- English (24) (remove)
Is part of the Bibliography
- yes (24) (remove)
Keywords
- Answer set programming (2)
- AODV (1)
- Ad hoc routing (1)
- Assessment (1)
- Backdoors (1)
- Bildung (1)
- Boolean logic models (1)
- Cluster Computing (1)
- Combinatorial multi-objective optimization (1)
- Computational complexity (1)
Institute
- Institut für Informatik und Computational Science (24) (remove)
Boolean networks provide a simple yet powerful qualitative modeling approach in systems biology. However, manual identification of logic rules underlying the system being studied is in most cases out of reach. Therefore, automated inference of Boolean logical networks from experimental data is a fundamental question in this field. This paper addresses the problem consisting of learning from a prior knowledge network describing causal interactions and phosphorylation activities at a pseudo-steady state, Boolean logic models of immediate-early response in signaling transduction networks. The underlying optimization problem has been so far addressed through mathematical programming approaches and the use of dedicated genetic algorithms. In a recent work we have shown severe limitations of stochastic approaches in this domain and proposed to use Answer Set Programming (ASP), considering a simpler problem setting. Herein, we extend our previous work in order to consider more realistic biological conditions including numerical datasets, the presence of feedback-loops in the prior knowledge network and the necessity of multi-objective optimization. In order to cope with such extensions, we propose several discretization schemes and elaborate upon our previous ASP encoding. Towards real-world biological data, we evaluate the performance of our approach over in silico numerical datasets based on a real and large-scale prior knowledge network. The correctness of our encoding and discretization schemes are dealt with in Appendices A-B. (C) 2014 Elsevier B.V. All rights reserved.
Formalizing informal logic
(2015)
In this paper we investigate the extent to which formal argumentation models can handle ten basic characteristics of informal logic identified in the informal logic literature. By showing how almost all of these characteristics can be successfully modelled formally, we claim that good progress can be made toward the project of formalizing informal logic. Of the formal argumentation models available, we chose the Carneades Argumentation System (CAS), a formal, computational model of argument that uses argument graphs as its basis, structures of a kind very familiar to practitioners of informal logic through their use of argument diagrams.
ProtoSense
(2015)