Biomedical subjects

Juha Kesseli

Publications and source records attributed to Juha Kesseli.

3 recordsLinked to original sources

PubMed2006

Iterated maps for annealed Boolean networks.

Boolean networks are used to study the large-scale properties of nonlinear systems and are mainly applied to model genetic regulatory networks. A statistical method called the annealed approximation is commonly used to examine the dynamical properties of randomly generated Boolean networks that are created with selected statistical features. However, in the literature there are several variations of the annealed approximation. These approximations cannot be interchangeably used in all cases due to different background assumptions. In this paper, we present the so-called four-state model, derive the different approximations from this model, and make the differences and connections between these approximations explicit. As an application of the presented results, we study the properties of the Boolean networks that are constructed with random functions, canalizing functions, and regulatory functions found in the biological literature.

Journal Article↗

PubMed2005

Tracking perturbations in Boolean networks with spectral methods.

In this paper we present a method for predicting the spread of perturbations in Boolean networks. The method is applicable to networks that have no regular topology. The prediction of perturbations can be performed easily by using a presented result which enables the efficient computation of the required iterative formulas. This result is based on abstract Fourier transform of the functions in the network. In this paper the method is applied to show the spread of perturbations in networks containing a distribution of functions found from biological data. The advances in the study of the spread of perturbations can directly be applied to enable ways of quantifying chaos in Boolean networks. Derrida plots over an arbitrary number of time steps can be computed and thus distributions of functions compared with each other with respect to the amount of order they create in random networks.

Journal Article↗

PubMed2005

Stability of functions in Boolean models of gene regulatory networks.

Boolean networks are used to model large nonlinear systems such as gene regulatory networks. We will present results that can be used to understand how the choice of functions affects the network dynamics. The so called bias-map and its fixed points depict much of the function's dynamical role in the network. We define the concept of stabilizing functions and show that many Post and canalizing functions are also stabilizing functions. Boolean networks constructed using the same type of stabilizing functions are always stable regardless of the average in-degree of network functions. We derive the number of all stabilizing functions and find it to be much larger than the number of Post and canalizing functions. We also discuss the implementation of functions and apply the presented results to biological data that give an approximation of the distribution of regulatory functions in eucaryotic cells. We find that the obtained theoretical results on the number of active genes are biologically plausible. Finally, based on the presented results, we discuss why canalizing and Post regulatory functions seem to be common in cells.

Adaptation, Physiological↗