M. Caselle

The Role of Incoherent MicroRNA-Mediated Feedforward Loops in Noise Buffering

MicroRNAs are endogenous non-coding RNAs which negatively regulate the expression of protein-coding genes in plants and animals. They are known to play an important role in several biological processes and, together with transcription factors, form a complex and highly interconnected regulatory network. Looking at the structure of this network, it is possible to recognize a few overrepresented motifs which are expected to perform important elementary regulatory functions. Among them, a special role is played by the microRNA-mediated feedforward loop in which a master transcription factor regulates a microRNA and, together with it, a set of target genes. In this paper we show analytically and through simulations that the incoherent version of this motif can couple the fine-tuning of a target protein level with an efficient noise control, thus conferring precision and stability to the overall gene expression program, especially in the presence of fluctuations in upstream regulators. Among the other results, a nontrivial prediction of our model is that the optimal attenuation of fluctuations coincides with a modest repression of the target expression. This feature is coherent with the expected fine-tuning function and in agreement with experimental observations of the actual impact of a wide class of microRNAs on the protein output of their targets. Finally, we describe the impact on noise-buffering efficiency of the cross-talk between microRNA targets that can naturally arise if the microRNA-mediated circuit is not considered as isolated, but embedded in a larger network of regulations.

String effects in the Wilson loop: A High precision numerical test

Abstract We test numerically the effective string description of the infrared limit of lattice gauge theories in the confining regime. We consider the 3D Z 2 lattice gauge theory, and we define ratios of Wilson loops such that the predictions of the effective string theory do not contain any adjustable parameters. In this way we are able to obtain a degree of accuracy high enough to show unambiguously that the flux-tube fluctuations are described, in the infrared limit, by an effective bosonic string theory.

String effects in the 3d gauge Ising model

We compare the predictions of the effective string description of confinement with a set of Montecarlo data for the 3d gauge Ising model at finite temperature. Thanks to a new algorithm which makes use of the dual symmetry of the model we can reach very high precisions even for large quark-antiquark distances. We are thus able to explore the large R regime of the effective string. We find that for large enough distances and low enough temperature the data are well described by a pure bosonic string. As the temperature increases higher order corrections become important and cannot be neglected even at large distances. These higher order corrections seem to be well described by the Nambu-Goto action truncated at the first perturbative order.

Static quark potential and effective string corrections in the (2+1)-d SU(2) Yang-Mills theory

We report on a very accurate measurement of the static quark potential in SU(2) Yang-Mills theory in (2+1) dimensions in order to study the corrections to the linear behaviour. We perform numerical simulations at zero and finite temperature comparing our results with the corrections given by the effective string picture in these two regimes. We also check for universal features discussing our results together with those recently published for the (2+1)-d (2) and SU(3) pure gauge theories.

Correlating overrepresented upstream motifs to gene expression: a computational approach to regulatory element discovery in eukaryotes

BackgroundGene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory elements in the upstream region of eukaryotic genes. The genes are grouped in sets sharing an overrepresented short motif in their upstream sequence. For each set, the average expression level from a microarray experiment is determined: If this level is significantly higher or lower than the average taken over the whole genome, then the overerpresented motif shared by the genes in the set is likely to play a role in their regulation.ResultsThe method was tested by applying it to the genome of Saccharomyces cerevisiae, using the publicly available results of a DNA microarray experiment, in which expression levels for virtually all the genes were measured during the diauxic shift from fermentation to respiration. Several known motifs were correctly identified, and a new candidate regulatory sequence was determined.ConclusionsWe have described and successfully tested a simple computational method to identify upstream motifs relevant to gene regulation in eukaryotes by studying the statistical correlation between overepresented upstream motifs and gene expression levels.

Random matrix theory and symmetric spaces

Abstract In this review we discuss the relationship between random matrix theories and symmetric spaces. We show that the integration manifolds of random matrix theories, the eigenvalue distribution, and the Dyson and boundary indices characterizing the ensembles are in strict correspondence with symmetric spaces and the intrinsic characteristics of their restricted root lattices. Several important results can be obtained from this identification. In particular the Cartan classification of triplets of symmetric spaces with positive, zero and negative curvature gives rise to a new classification of random matrix ensembles. The review is organized into two main parts. In Part I the theory of symmetric spaces is reviewed with particular emphasis on the ideas relevant for appreciating the correspondence with random matrix theories. In Part II we discuss various applications of symmetric spaces to random matrix theories and in particular the new classification of disordered systems derived from the classification of symmetric spaces. We also review how the mapping from integrable Calogero–Sutherland models to symmetric spaces can be used in the theory of random matrices, with particular consequences for quantum transport problems. We conclude indicating some interesting new directions of research based on these identifications.

Regge calculus as a local theory of the Poincaré group

Abstract We reformulate Regge calculus in terms of dynamical variables belonging to the Poincare group. Our formulation uses the dual lattice, is naturally related in the continuum limit to the Einstein action written in terms of differential forms, and retains and possibility of choosing between the first order and the second order formalism.

Width of long colour flux tubes in lattice gauge systems

Abstract In the confining phase of any gauge system the mean squared width of the colour flux tube joining a pair of quarks should grow logarithmically as a function of their distance, according to the effective string description of its infrared properties. New data on 3D 7L2 gauge theory, combined with high precision data on the interface physics of the 3D Ising model, nicely fit this behaviour over a range of more than two orders of magnitude.In the confining phase of any gauge system the mean squared width of the colour flux tube joining a pair of quarks should grow logarithmically as a function of their distance, according to the effective string description of its infrared properties. New data on 3D Z_2 gauge theory, combined with high precision data on the interface physics of the 3D Ising model fit nicely this behaviour over a range of more than two orders of magnitude.

Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrep-resented upstream motifs

BackgroundTranscriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made easier by the fact that they often appear several times in the upstream region of the regulated genes, so that the number of occurrences of relevant motifs is often significantly larger than expected by pure chance.ResultsTo exploit this fact, we construct sets of genes characterized by the statistical overrepresentation of a certain motif in their upstream regions. Then we study the functional characterization of these sets by analyzing their annotation to Gene Ontology terms. For the sets showing a statistically significant specific functional characterization, we conjecture that the upstream motif characterizing the set is a binding site for a transcription factor involved in the regulation of the genes in the set.ConclusionsThe method we propose is able to identify many known binding sites in S. cerevisiae and new candidate targets of regulation by known transcritpion factors. Its application to less well studied organisms is likely to be valuable in the exploration of their regulatory interaction network.

The interface free energy: comparison of accurate Monte Carlo results for the 3D Ising model with effective interface models

We provide accurate Monte Carlo results for the free energy of interfaces with periodic boundary conditions in the 3D Ising model. We study a large range of inverse temperatures, allowing to control corrections to scaling. In addition to square interfaces, we study rectangular interfaces for a large range of aspect ratios u = L1/L2. Our numerical results are compared with predictions of effective interface models. This comparison verifies clearly the effective Nambu-Goto model up to two-loop order. Our data also allow us to obtain the estimates Tc/(?)1/2 = 1.235(2), m0++/(?)1/2 = 3.037(16) and R+ = f+2?0 = 0.387(2), which are more precise than previous ones.