Article

Deterministic and stochastic models of genetic regulatory networks.

Institute for Systems Biology, Seattle, Washington, USA.
Methods in enzymology (Impact Factor: 2.19). 01/2009; 467:335-56. DOI: 10.1016/S0076-6879(09)67013-0
Source: PubMed

ABSTRACT Traditionally molecular biology research has tended to reduce biological pathways to composite units studied as isolated parts of the cellular system. With the advent of high throughput methodologies that can capture thousands of data points, and powerful computational approaches, the reality of studying cellular processes at a systems level is upon us. As these approaches yield massive datasets, systems level analyses have drawn upon other fields such as engineering and mathematics, adapting computational and statistical approaches to decipher relationships between molecules. Guided by high quality datasets and analyses, one can begin the process of predictive modeling. The findings from such approaches are often surprising and beyond normal intuition. We discuss four classes of dynamical systems used to model genetic regulatory networks. The discussion is divided into continuous and discrete models, as well as deterministic and stochastic model classes. For each combination of these categories, a model is presented and discussed in the context of the yeast cell cycle, illustrating how different types of questions can be addressed by different model classes.

0 Followers
 · 
70 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Modern biology will never be the same without mathematical and computational tools. Using mind map with "epigenetics" as the root, we discuss the current advancement in the field of biomathematics for modeling cell-fate specification. In the discussions, we also present possible directions for future research. To cite this article: Jomar Fajardo Rabajante, et al. Mathematical modeling of cell-fate specification: From simple to complex epigenetics. Stem Cell Epigenetics 2015; 2: e752. doi: 10.14800/sce.752.
  • Genome Bioinformatics and Computational Biology, Edited by Renu Tuteja, 01/2012: chapter Phylogenomics; Nova Science., ISBN: 9781621009252
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The epigenetic pathway of a cell as it differentiates from a stem cell state to a mature lineage-committed one has been historically understood in terms of Waddington's landscape, consisting of hills and valleys. The smooth top and valley-strewn bottom of the hill represent their undifferentiated and differentiated states, respectively. Although mathematical ideas rooted in nonlinear dynamics and bifurcation theory have been used to quantify this picture, the importance of time delays arising from multistep chemical reactions or cellular shape transformations have been ignored so far. We argue that this feature is crucial in understanding cell differentiation and explore the role of time delay in a model of a single-gene regulatory circuit. We show that the interplay of time-dependent drive and delay introduces a new regime where the system shows sustained oscillations between the two admissible steady states. We interpret these results in the light of recent perplexing experiments on inducing the pluripotent state in mouse somatic cells. We also comment on how such an oscillatory state can provide a framework for understanding more general feedback circuits in cell development.
    Journal of The Royal Society Interface 11/2014; 11(100). DOI:10.1098/rsif.2014.0706 · 3.86 Impact Factor

Full-text (2 Sources)

Download
112 Downloads
Available from
May 21, 2014