Breast Cancer is reckoned amongst the most common cause of morbidity and mortality among women, adversely affecting female population irrespective age. The poor survival rate reported in invasive carcinoma cases demands identification early developmental stage key markers. MicroRNAs are contributing a critical role gene regulation potential Over 2000 miRNAs have been identified considered to of...

Many methods have been developed for reverse engineering gene networks from time series expression data. However, when the number of genes and the complexity of regulation increase, it becomes increasingly difficult to infer gene networks. To tackle this scalability problem, this study presents an approach with two phases: gene clustering and network reconstruction. To perform gene clustering, ...

background: it is now well-demonstrated that histone demethylases play an important role in developmental controls, cell-fate decisions, and a variety of diseases such as cancer. lysine-specific demethylase 5d (kdm5d) is a male-specific histone demethylase that specifically demethylates di- and tri-methyl h3k4 at the start site of active genes. in this light, the aim of this study was to invest...

The inference of gene regulatory network from expression data is an important area of research that provides insight to the inner workings of a biological system. The relevance-network-based approaches provide a simple and easily-scalable solution to the understanding of interaction between genes. Up until now, most works based on relevance network focus on the discovery of direct regulation us...

We examine how different transcriptional network structures can evolve from an ancestral network. By characterizing how the ancestral mode of gene regulation for genes specific to a-type cells in yeast species evolved from an activating paradigm to a repressing one, we show that regulatory protein modularity, conversion of one cis-regulatory sequence to another, distribution of binding energy a...

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally cap...

Construction of genome-scale models of metabolic networks is an important problem in systems biology. Most of the studies of metabolic networks have focused of steady state flows in the native and mutated networks. However, to understand cellular adaptation and development, regulation of metabolism have to be taken into account. The approach of system biology would be to consider metabolism in ...