PURPOSE To compare the performance of newly proposed point-wise linear regression (PLR) with the binomial test (binomial PLR) against mean deviation (MD) trend analysis and permutation analyses of PLR (PoPLR), in detecting global visual field (VF) progression in glaucoma. METHODS 15 VFs (Humphrey Field Analyzer, SITA standard, 24-2) were collected from 96 eyes of 59 open angle glaucoma patien...

Boolean networks form a class of disordered dynamical systems that have been studied in physics owing to their relationships with disordered systems in statistical mechanics and in biology as models of genetic regulatory networks. Recently they have been generalized to probabilistic Boolean networks (PBNs) to facilitate the incorporation of uncertainty in the model and to represent cellular con...

This paper proposes new analysis techniques for Bayes networks in which conditional probability tables (CPTs) may contain symbolic variables. The key idea is to exploit scalable and powerful synthesis problems parametric Markov chains. Our are applicable arbitrarily many, possibly dependent, parameters that occur multiple CPTs. lifts the severe restrictions on parameters, e.g., by restricting n...

The IEEE 802.1 Provider Backbone Bridges (PBBs) specification defines an architecture and bridge protocols for interconnection of multiple Provider Bridged Networks (PBNs). Provider backbone bridging was defined by IEEE as a connectionless technology based on multipoint VLAN tunnels. PBB can be used to attain better scalability than Provider Bridges (PBs) in terms of the number of customer Medi...

MOTIVATION A major objective of gene regulatory network modeling, in addition to gaining a deeper understanding of genetic regulation and control, is the development of computational tools for the identification and discovery of potential targets for therapeutic intervention in diseases such as cancer. We consider the general question of the potential effect of individual genes on the global dy...

In this paper we envisage building Probabilistic Boolean Networks (PBNs) from a prescribed stationary distribution. This is an inverse problem of huge size that can be subdivided into two parts — viz. (i) construction of a transition probability matrix from a given stationary distribution (Problem ST), and (ii) construction of a PBN from a given transition probability matrix (Problem TP). A gen...

MOTIVATION Probabilistic Boolean networks (PBNs) have been proposed to model genetic regulatory interactions. The steady-state probability distribution of a PBN gives important information about the captured genetic network. The computation of the steady-state probability distribution usually includes construction of the transition probability matrix and computation of the steady-state probabil...

Many mathematical models for gene regulatory networks have been proposed. In this study, the authors study attractors in probabilistic Boolean networks (PBNs). They study the expected number of singleton attractors in a PBN and show that it is (2 - (1/2)(L-1))(n), where n is the number of nodes in a PBN and L is the number of Boolean functions assigned to each node. In the case of L=2, this num...