Neural encoding: the brain's representation of space.
Recent studies have shown that a part of the brain makes use of a grid of equilateral triangles to encode the location of the animal within the local environment.
Animals↗
Biomedical subjects
Ruadhan A O'Flanagan
Publications and source records attributed to Ruadhan A O'Flanagan.
Optimal path to epigenetic switching.
We use large deviation methods to calculate rates of noise-induced transitions between states in multistable genetic networks. We analyze a synthetic biochemical circuit, the toggle switch, and compare the results to those obtained from a numerical solution of the master equation.
Adaptation, Physiological↗
Repression of the yeast HO gene by the MATalpha2 and MATa1 homeodomain proteins.
The HO gene in Saccharomyces cerevisiae is regulated by a large and complex promoter that is similar to promoters in higher order eukaryotes. Within this promoter are 10 potential binding sites for the a1-alpha2 heterodimer, which represses HO and other haploid-specific genes in diploid yeast cells. We have determined that a1-alpha2 binds to these sites with differing affinity, and that while certain strong-affinity sites are crucial for repression of HO, some of the weak-affinity sites are dispensable. However, these weak-affinity a1-alpha2-binding sites are strongly conserved in related yeast species and have a role in maintaining repression upon the loss of strong-affinity sites. We found that these weak sites are sufficient for a1-alpha2 to partially repress HO and recruit the Tup1-Cyc8 (Tup1-Ssn6) co-repressor complex to the HO promoter. We demonstrate that the Swi5 activator protein is not bound to URS1 in diploid cells, suggesting that recruitment of the Tup1-Cyc8 complex by a1-alpha2 prevents DNA binding by activator proteins resulting in repression of HO.
Base Sequence↗
Combined analysis of expression data and transcription factor binding sites in the yeast genome.
BACKGROUND: The analysis of gene expression using DNA microarrays provides genome wide profiles of the genes controlled by the presence or absence of a specific transcription factor. However, the question arises of whether a change in the level of transcription of a specific gene is caused by the transcription factor acting directly at the promoter of the gene or through regulation of other transcription factors working at the promoter. RESULTS: To address this problem we have devised a computational method that combines microarray expression and site preference data. We have tested this approach by identifying functional targets of the a1-alpha2 complex, which represses haploid-specific genes in the yeast Saccharomyces cerevisiae. Our analysis identified many known or suspected haploid-specific genes that are direct targets of the a1-alpha2 complex, as well as a number of previously uncharacterized targets. We were also able to identify a number of haploid-specific genes which do not appear to be direct targets of the a1-alpha2 complex, as well as a1-alpha2 target sites that do not repress transcription of nearby genes. Our method has a much lower false positive rate when compared to some of the conventional bioinformatic approaches. CONCLUSIONS: These findings show advantages of combining these two forms of data to investigate the mechanism of co-regulation of specific sets of genes.
Algorithms↗