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A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for(More)
Several recent studies have utilized respondent-driven sampling (RDS) methods to survey hidden populations such as commercial sex-workers, men who have sex with men (MSM) and injection drug users (IDU). Few studies, however, have provided a direct comparison between RDS and other more traditional sampling methods such as venue-based, targeted or time/space(More)
Boolean Networks are emerging as a simple yet powerful formalism to model and study Gene Regulatory Networks. Nevertheless, the most widely used Boolean Network-based models do not include any post-transcriptional regulation mechanism. In this paper we discuss how the post-transcriptional regulation mechanism mediated by miRNAs can be included in a Boolean(More)
The present study was undertaken to appraise the role of selenium priming for improving emergence and seedling growth of basmati rice. Seeds of two fine rice cultivars (Super and Shaheen Basmati) were primed with concentrations of 15, 30, 45, 60, 75, 90, and 105 μmol L−1 selenium. Untreated dry- and hydro-primed seeds were maintained as the control and(More)
Amongst naturally occurring plant growth stimulants, moringa (Moringa oleifera Lam.) has attained enormous attention being rich in cytokinin, antioxidants and macro–micro nutrients in its leaves. In this study, potential of foliar applied moringa leaf extract (MLE; 30 times diluted), benzyl amino purine (BAP; 50 mg L−1) and hydrogen peroxide (H2O2; 120 μM)(More)
Keywords: MiRNA Gene regulatory networks Post-transcriptional regulation Boolean networks Complex systems Network analysis a b s t r a c t Gene regulatory networks (GRNs) model some of the mechanisms that regulate gene expression. Among the computational approaches available to model and study GNRs, Boolean network (BN) emerged as very successful to better(More)
Today large scale genome sequencing technologies are uncovering an increasing amount of new genes and proteins, which remain uncharacterized. Experimental procedures for protein function prediction are low throughput by nature and thus can't be used to keep up with the rate at which new proteins are discovered. On the other hand, proteins are the prominent(More)