682 research outputs found
Intersecting Families of Permutations
A set of permutations is said to be {\em k-intersecting} if
any two permutations in agree on at least points. We show that for any
, if is sufficiently large depending on , then the
largest -intersecting subsets of are cosets of stabilizers of
points, proving a conjecture of Deza and Frankl. We also prove a similar result
concerning -cross-intersecting subsets. Our proofs are based on eigenvalue
techniques and the representation theory of the symmetric group.Comment: 'Erratum' section added. Yuval Filmus has recently pointed out that
the 'Generalised Birkhoff theorem', Theorem 29, is false for k > 1, and so is
Theorem 27 for k > 1. An alternative proof of the equality part of the
Deza-Frankl conjecture is referenced, bypassing the need for Theorems 27 and
2
A catalog of stability-associated sequence elements in 3' UTRs of yeast mRNAs
BACKGROUND: In recent years, intensive computational efforts have been directed towards the discovery of promoter motifs that correlate with mRNA expression profiles. Nevertheless, it is still not always possible to predict steady-state mRNA expression levels based on promoter signals alone, suggesting that other factors may be involved. Other genic regions, in particular 3' UTRs, which are known to exert regulatory effects especially through controlling RNA stability and localization, were less comprehensively investigated, and deciphering regulatory motifs within them is thus crucial. RESULTS: By analyzing 3' UTR sequences and mRNA decay profiles of Saccharomyces cerevisiae genes, we derived a catalog of 53 sequence motifs that may be implicated in stabilization or destabilization of mRNAs. Some of the motifs correspond to known RNA-binding protein sites, and one of them may act in destabilization of ribosome biogenesis genes during stress response. In addition, we present for the first time a catalog of 23 motifs associated with subcellular localization. A significant proportion of the 3' UTR motifs is highly conserved in orthologous yeast genes, and some of the motifs are strikingly similar to recently published mammalian 3' UTR motifs. We classified all genes into those regulated only at transcription initiation level, only at degradation level, and those regulated by a combination of both. Interestingly, different biological functionalities and expression patterns correspond to such classification. CONCLUSION: The present motif catalogs are a first step towards the understanding of the regulation of mRNA degradation and subcellular localization, two important processes which - together with transcription regulation - determine the cell transcriptome
No nonlocal box is universal
We show that standard nonlocal boxes, also known as Popescu-Rohrlich
machines, are not sufficient to simulate any nonlocal correlations that do not
allow signalling. This was known in the multipartite scenario, but we extend
the result to the bipartite case. We then generalize this result further by
showing that no finite set containing any finite-output-alphabet nonlocal boxes
can be a universal set for nonlocality.Comment: Additions to the acknowledgements sectio
Messenger RNA Fluctuations and Regulatory RNAs Shape the Dynamics of Negative Feedback Loop
Single cell experiments of simple regulatory networks can markedly differ
from cell population experiments. Such differences arise from stochastic events
in individual cells that are averaged out in cell populations. For instance,
while individual cells may show sustained oscillations in the concentrations of
some proteins, such oscillations may appear damped in the population average.
In this paper we investigate the role of RNA stochastic fluctuations as a
leading force to produce a sustained excitatory behavior at the single cell
level. Opposed to some previous models, we build a fully stochastic model of a
negative feedback loop that explicitly takes into account the RNA stochastic
dynamics. We find that messenger RNA random fluctuations can be amplified
during translation and produce sustained pulses of protein expression.
Motivated by the recent appreciation of the importance of non--coding
regulatory RNAs in post--transcription regulation, we also consider the
possibility that a regulatory RNA transcript could bind to the messenger RNA
and repress translation. Our findings show that the regulatory transcript helps
reduce gene expression variability both at the single cell level and at the
cell population level.Comment: 87.18.Vf --> Systems biology 87.10.Mn --> Stochastic models in
biological systems 87.18.Tt --> Noise in biological systems
http://www.ncbi.nlm.nih.gov/pubmed/20365787
http://www.weizmann.ac.il/complex/tlusty/papers/PhysRevE2010.pd
The role of codon selection in regulation of translation efficiency deduced from synthetic libraries
Extraction of transcription regulatory signals from genome-wide DNA–protein interaction data
Deciphering gene regulatory network architecture amounts to the identification of the regulators, conditions in which they act, genes they regulate, cis-acting motifs they bind, expression profiles they dictate and more complex relationships between alternative regulatory partnerships and alternative regulatory motifs that give rise to sub-modalities of expression profiles. The ‘location data’ in yeast is a comprehensive resource that provides transcription factor–DNA interaction information in vivo. Here, we provide two contributions: first, we developed means to assess the extent of noise in the location data, and consequently for extracting signals from it. Second, we couple signal extraction with better characterization of the genetic network architecture. We apply two methods for the detection of combinatorial associations between transcription factors (TFs), the integration of which provides a global map of combinatorial regulatory interactions. We discover the capacity of regulatory motifs and TF partnerships to dictate fine-tuned expression patterns of subsets of genes, which are clearly distinct from those displayed by most genes assigned to the same TF. Our findings provide carefully prioritized, high-quality assignments between regulators and regulated genes and as such should prove useful for experimental and computational biologists alike
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