Institut für Informatik und Computational Science
Refine
Year of publication
- 2019 (21) (remove)
Document Type
- Article (10)
- Doctoral Thesis (4)
- Other (4)
- Postprint (3)
Language
- English (21)
Is part of the Bibliography
- yes (21)
Keywords
- Equilibrium logic (3)
- answer set programming (3)
- Answer Set Programming (2)
- Answer set programming (2)
- Non-monotonic reasoning (2)
- automatic feedback (2)
- lesson planning (2)
- lesson preparation (2)
- support system (2)
- Aggregates (1)
- Android Security (1)
- Argumentation (1)
- Augenbewegungen (1)
- Beweis (1)
- Beweisassistent (1)
- Beweisumgebung (1)
- Bot Detection (1)
- Computer security (1)
- Coq (1)
- Curry (1)
- Customer ownership (1)
- Denotational semantics (1)
- Digitalization (1)
- Emotionen (1)
- Emotionsforschung (1)
- Entity Linking (1)
- Explicit negation (1)
- Forgetting (1)
- Formalismus (1)
- Formalitätsgrad (1)
- GERBIL (1)
- Gesichtsausdruck (1)
- Graph Convolutional Neural Networks (1)
- Graph Embedding (1)
- Https traffic (1)
- Insurance industry (1)
- Logik (1)
- Machine learning (1)
- Mathematikdidaktik (1)
- Mathematikphilosophie (1)
- Multi-sided platforms (1)
- Neural networks (1)
- OSSE (1)
- Objektive Schwierigkeit (1)
- Privacy Protection (1)
- SWOT (1)
- Social Media Analysis (1)
- Static Analysis (1)
- Strong equivalence (1)
- Taktik (1)
- Traffic data (1)
- Value network (1)
- Wahrnehmung (1)
- Wahrnehmung von Arousal (1)
- Wahrnehmungsunterschiede (1)
- action and change (1)
- argumentation (1)
- arousal perception (1)
- automated planning (1)
- benchmark (1)
- bioinformatics (1)
- biometrics (1)
- biometrische Identifikation (1)
- computational methods (1)
- computergestützte Methoden (1)
- correlated errors (1)
- degree of formality (1)
- detrending (1)
- emotion (1)
- emotion representation (1)
- emotion research (1)
- ensemble kalman filter (1)
- epistemic logic programs (1)
- epistemic specifications (1)
- evaluation (1)
- explicit negation (1)
- eye movements (1)
- face tracking (1)
- facial expression (1)
- formalism (1)
- gap-filling (1)
- hybrid solving (1)
- knowledge representation and nonmonotonic reasoning (1)
- linear programming (1)
- logic (1)
- mathematics education (1)
- metabolic network (1)
- non-monotonic reasoning (1)
- objective difficulty (1)
- perception (1)
- perception differences (1)
- philosophy of mathematics (1)
- probabilistic deep learning (1)
- probabilistic deep metric learning (1)
- probabilistische tiefe neuronale Netze (1)
- probabilistisches tiefes metrisches Lernen (1)
- projection (1)
- proof (1)
- proof assistant (1)
- proof environment (1)
- tactic (1)
- technical notes and rapid communications (1)
Institute
Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system dingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli. Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches.