Circadian control of abscisic acid biosynthesis and signalling pathways revealed by genome-wide analysis of LHY binding targets.

The LATE ELONGATED HYPOCOTYL (LHY) transcription factor functions as part of the oscillatory mechanism of the Arabidopsis circadian clock. This paper reports the genome-wide analysis of its binding targets and reveals a role in the control of abscisic acid (ABA) biosynthesis and downstream responses. LHY directly repressed expression of 9-cis-epoxycarotenoid dioxygenase enzymes, which catalyse the rate-limiting step of ABA biosynthesis.

Emerging design principles in the Arabidopsis circadian clock.

Recent experimental advances have enabled the identification of direct regulatory targets for transcription factors. Application of these techniques to the circadian regulatory network in Arabidopsis has uncovered a number of discrepancies within established models as well as novel regulatory interactions. This review integrates these new findings and discusses the functional implications of the revised transcriptional network for the oscillatory mechanism of the clock.

The genotype-phenotype relationship in multicellular pattern-generating models--the neglected role of pattern descriptors.

Background: A deep understanding of what causes the phenotypic variation arising from biological patterning processes, cannot be claimed before we are able to recreate this variation by mathematical models capable of generating genotype-phenotype maps in a causally cohesive way. However, the concept of pattern in a multicellular context implies that what matters is not the state of every single cell, but certain emergent qualities of the total cell aggregate. Thus, in order to set up a genotype-phenotype map in such a spatiotemporal pattern setting one is actually forced to establish new pattern descriptors and derive their relations to parameters of the original model.

Analysis of gene regulatory network models with graded and binary transcriptional responses.

The steep sigmoid framework developed by Plahte and Kjøglum [Plahte, E., Kjøglum, S., 2005.

Priming nonlinear searches for pathway identification.

Background: Dense time series of metabolite concentrations or of the expression patterns of proteins may be available in the near future as a result of the rapid development of novel, high-throughput experimental techniques. Such time series implicitly contain valuable information about the connectivity and regulatory structure of the underlying metabolic or proteomic networks. The extraction of this information is a challenging task because it usually requires nonlinear estimation methods that involve iterative search algorithms.