TY  - JOUR
A1  - Videla, Santiago
A1  - Guziolowski, Carito
A1  - Eduati, Federica
A1  - Thiele, Sven
A1  - Gebser, Martin
A1  - Nicolas, Jacques
A1  - Saez-Rodriguez, Julio
A1  - Schaub, Torsten H.
A1  - Siegel, Anne
T1  - Learning Boolean logic models of signaling networks with ASP
JF  - Theoretical computer science
N2  - 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.
KW  - Answer set programming
KW  - Signaling transduction networks
KW  - Boolean logic models
KW  - Combinatorial multi-objective optimization
KW  - Systems biology
Y1  - 2015
U6  - https://doi.org/10.1016/j.tcs.2014.06.022
SN  - 0304-3975
SN  - 1879-2294
VL  - 599
SP  - 79
EP  - 101
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Walton, Douglas
A1  - Gordon, Thomas F.
T1  - Formalizing informal logic
JF  - Informal logic : reasoning and argumentation in theory and practics
N2  - 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.
KW  - informal logic
KW  - formal argumentation systems
KW  - real arguments
KW  - premise acceptability
KW  - conductive argument
KW  - RSA triangle
KW  - relevance
KW  - sufficiency
Y1  - 2015
SN  - 0824-2577
VL  - 35
IS  - 4
SP  - 508
EP  - 538
PB  - Centre for Research in Reasoning, Argumentation and Rhetoric, University of Windsor
CY  - Windsor
ER  - 
TY  - JOUR
A1  - Wegner, Christian
A1  - Zender, Raphael
A1  - Lucke, Ulrike
T1  - ProtoSense
BT  - Interactive Paper Prototyping with Multi-Touch Tables
JF  - KEYCIT 2014 - Key Competencies in Informatics and ICT
KW  - Interface design
KW  - paper prototyping
KW  - NUI
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-82970
SN  - 1868-0844
SN  - 2191-1940
IS  - 7
SP  - 405
EP  - 407
PB  - Universitätsverlag Potsdam
CY  - Potsdam
ER  - 
TY  - THES
A1  - Wust, Johannes
T1  - Mixed workload managment for in-memory databases
BT  - executing mixed workloads of enterprise applications with TAMEX
Y1  - 2015
ER  -