A declarative constraint-based method for analyzing discrete genetic regulatory networks.
Biosystems
; 98(2): 91-104, 2009 Nov.
Article
em En
| MEDLINE
| ID: mdl-19664681
ABSTRACT
Dynamical modeling has proven useful for understanding how complex biological processes emerge from the many components and interactions composing genetic regulatory networks (GRNs). However, the development of models is hampered by large uncertainties in both the network structure and parameter values. To remedy this problem, the models are usually developed through an iterative process based on numerous simulations, confronting model predictions with experimental data and refining the model structure and/or parameter values to repair the inconsistencies. In this paper, we propose an alternative to this generate-and-test approach. We present a four-step method for the systematic construction and analysis of discrete models of GRNs by means of a declarative approach. Instead of instantiating the models as in classical modeling approaches, the biological knowledge on the network structure and its dynamics is formulated in the form of constraints. The compatibility of the network structure with the constraints is queried and in case of inconsistencies, some constraints are relaxed. Common properties of the consistent models are then analyzed by means of dedicated languages. Two such languages are introduced in the paper. Removing questionable constraints or adding interesting ones allows to further analyze the models. This approach allows to identify the best experiments to be carried out, in order to discriminate sets of consistent models and refine our knowledge on the system functioning. We test the feasibility of our approach, by applying it to the re-examination of a model describing the nutritional stress response in the bacterium Escherichia coli.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Redes Reguladoras de Genes
/
Modelos Genéticos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2009
Tipo de documento:
Article