Motivation: The topology and function of gene regulation networks are commonly inferred from time series of gene expression levels in cell populations. This strategy is usually invalid if the gene expression in different cells of the population is not synchronous. A promising, though technically more demanding alternative is therefore to measure the gene expression levels in single cells indivi...

Many years of experimental and computational molecular biology of model organisms such as Escherichia coli and Saccharomyces cerevisiae has elucidated the gene regulatory network in these organisms. Relatively little is known about gene regulation in species other than the model organisms, whether gene regulatory networks are conserved, and to what degree our knowledge based on model organisms ...

background: treatment of cutaneous leishmaniasis (cl) is being faced with serious difficulties in fars province, due to emerging of resistance against meglumine antimonite (glucantime®). in this context, determining some biomarkers for drug sensitivity monitoring seems to be highly essential. different studies have been carried out to decipher the genes might be involved in antimony resistant p...

As an aromatic and colorful plant of substantive taste, saffron (Crocus sativus L.) owes such properties of matter to growing class of the secondary metabolites derived from the carotenoids, apocarotenoids. Regarding the critical role of microRNAs in secondary metabolic synthesis and the limited number of identified miRNAs in C. sativus, on the other hand, one may see the point how the characte...

Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, protein or RNA transport. Thus, learning gene network is a crucial problem in the post genome era. Most existing works learn gene networks by assuming one gene provokes the expression of another gene directly leading to an over-simplified model. In this pa...

Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, learning gene network is a crucial problem in the post genome era. Most existing works learn gene networks by assuming one gene provokes the expression of another gene directly leading to an over-simplified model. In thi...

The genetic bases of complex traits often involve multiple inherited genetic factors that function in a network basis. By promoting or reducing the expression of functional genes that are directly or indirectly related to a trait, gene regulation has been proposed as a major determinant of trait variation. The combined analysis of genetic and gene expression data, termed genetical genomics anal...

Reconstructing gene network structure from Microarray time-series data is a basic problem in Systems Biology. In gene regulation networks, the time delays and the combination effects which are not considered by most existent models are key factors to understand the genetic regulatory networks. To address these problems, this paper proposed a fast algorithm to learn initial network structures fo...

Although all human tissues carry out common processes, tissues are distinguished by gene expression patterns, implying that distinct regulatory programs control tissue specificity. In this study, we investigate gene expression and regulation across 38 tissues profiled in the Genotype-Tissue Expression project. We find that network edges (transcription factor to target gene connections) have hig...

Understanding organisms from a systems perspective is essential for predicting cellular behaviour as well as designing gene-metabolic circuits for novel functions. The structure, dynamics and interactions of cellular networks are all vital components of systems biology. To facilitate investigation of these aspects, we have developed an integrative technique called network component analysis, wh...