Several mathematical models have been proposed to predict the activation state of a transcription factor (TF) from the expression levels of its target genes. This inference problem is complicated however due to the fact that different genes may be regulated by different activation schemes...

High-gain nonlinear observers occur in the nonlinear automatic control theory and are in standard usage in chemical engineering processes. We apply such a type of analysis in the context of a very simple one-gene regulation circuit. In general, an observer combines an analytical...

We present the Ontocancro Database (www.ontocancro.org) illustrated with applications to network modeling and pathway functional analysis. The database compiles information on gene pathways involved in Human Genome Maintenance Mechanisms (GMM) whose dysfunction accounts for cancer and several...

The activity of the cell is often coordinated by the organisation of proteins into regulatory circuits that share a common function. Genome-wide expression profiles might contain important information on these circuits. Current approaches for the analysis of gene expression data include...

We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any...

Many theoretical models have recently been proposed to understand the structure of cellular systems composed of various types of elements (e.g., proteins, metabolites and genes) and their interactions. However, the cell is a highly dynamic system with thousands of functional elements fluctuating...

A number of microarray studies assume gene expression data to be independent of one another. In this report, we provide evidence of correlation in cDNA microarray gene expression data using classical power spectral analysis and the sophisticated detrended fluctuation analysis (DFA). Such...

Arrays allow simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify sets of genes with similar profiles. We show that information theoretic methods are capable of modeling and assessing dissimilarities between the dynamics underlying to the...

This paper introduces a new concept of least community that is as homogeneous as a random graph, and develops a new community detection algorithm from the perspective of homogeneity or heterogeneity. Based on this concept, we adopt head/tail breaks–a newly developed classification scheme for...

Identifying the community structure in a complex network has been addressed in many different ways. In this paper, the simulated annealing strategy is used to maximize the modularity of a network, associating with a dissimilarity-index-based and with a diffusion-distance-based k-means iterative...