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In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between

conservation in regulatory regions and with generation of full-length open reading frames. Patterns of AS and APA were strongly correlated across tissues, suggesting coordinated regulation of these processes, and sequence conservation of a subset of known regulatory motifs in both alternative introns and 3

People approach pleasure and avoid pain. To discover the true nature of approach-avoidance motivation, psychologists need to move beyond this hedonic principle to the principles that underlie the different ways that it operates. One such principle is regulatory focus, which distinguishes self-regulation

MicroRNAs (miRNAs) constitute a large family of noncod-ing RNAs that function as guide molecules in diverse gene silencing pathways. Current efforts are focused on the regulatory function of miRNAs, while little is known about how these unusual genes themselves are regulated. Here we present

DNA cytosine methylation is a central epigenetic modification that has essential roles in cellular processes including genome regulation, development and disease. Here we present the first genome-wide, single-base-resolution maps of methylated cytosines in a mammalian genome, from both human

to self-regulatory failure. A strength model of self-regulation fits the data better than activation, priming, skill, or constant capacity models of self-regulation. The capacity of the human organism to override, interrupt, and otherwise alter its own responses is one of the most dramatic and impressive

Using a process model of emotion, a distinction between antecedent-focused and response-focused emotion regulation is proposed. To test this distinction, 120 participants were shown a disgusting film while their experiential, behavioral, and physiological responses were recorded. Participants were

of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various

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