http://www.cnr.it/ontology/cnr/individuo/prodotto/ID31468
A computational framework for qualitative simulation of nonlinear dynamical models of gene-regulatory networks (Articolo in rivista)
- Type
- Label
- A computational framework for qualitative simulation of nonlinear dynamical models of gene-regulatory networks (Articolo in rivista) (literal)
- Anno
- 2009-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1186/1471-2105-10-S12-S14 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Ironi L.; Panzeri L. (literal)
- Pagina inizio
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- PubMe (literal)
- Scopu (literal)
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Istituto di Matematica Applicata e Tecnologie Informatiche (literal)
- Titolo
- A computational framework for qualitative simulation of nonlinear dynamical models of gene-regulatory networks (literal)
- Abstract
- Background: Due to the huge amount of information at genomic level made recently available by
high-throughput experimental technologies, networks of regulatory interactions between genes and
gene products, the so-called gene-regulatory networks, can be uncovered. Most networks of interest
are quite intricate because of both the high dimension of interacting elements and the complexity of
the kinds of interactions between them. Then, mathematical and computational modeling
frameworks are a must to predict the network behavior in response to environmental stimuli.
A specific class of Ordinary Differential Equations (ODE) has shown to be adequate to describe the
essential features of the dynamics of gene-regulatory networks. But, deriving quantitative predictions
of the network dynamics through the numerical simulation of such models is mostly impracticable as
they are currently characterized by incomplete knowledge of biochemical reactions underlying
regulatory interactions, and of numeric values of kinetic parameters.
Results: This paper presents a computational framework for qualitative simulation of a class of
ODE models, based on the assumption that gene regulation is threshold-dependent, i.e. only
effective above or below a certain threshold. The simulation algorithm we propose assumes that
threshold-dependent regulation mechanisms are modeled by continuous steep sigmoid functions,
unlike other simulation tools that considerably simplifies the problem by approximating threshold regulated
response functions by step functions discontinuous in the thresholds. The algorithm
results from the interplay between methods to deal with incomplete knowledge and to study
phenomena that occur at different time-scales.
Conclusion: The work herein presented establishes the computational groundwork for a sound
and a complete algorithm capable to capture the dynamical properties that depend only on the
network structure and are invariant for ranges of values of kinetic parameters. At the current state
of knowledge, the exploitation of such a tool is rather appropriate and useful to understand how
specific activity patterns derive from given network structures, and what different types of
dynamical behaviors are possible. (literal)
- Editore
- Prodotto di
- Autore CNR
- Insieme di parole chiave
Incoming links:
- Autore CNR di
- Prodotto
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
- Editore di
- Insieme di parole chiave di