Evidence for transcript networks composed of chimeric RNAs in human cells.

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.

Fast numerical algorithms for the computation of invariant tori in Hamiltonian systems

In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.

CD28/CTLA4-B7 interaction is dispensable for T cell stimulation by mouse mammary tumor virus superantigen but not for B cell differentiation and virus dissemination.

B cells are the primary targets of infection for mouse mammary tumor virus (MMTV). However, for productive retroviral infection, T cell stimulation through the virally-encoded superantigen (SAG) is necessary. It activates B cells and leads to cell division and differentiation. To characterize the role of B cell differentiation for the MMTV life cycle, we studied the course of infection in transgenic mice deficient for CD28/CTLA4-B7 interactions (mCTLA4-H gamma 1 transgenic mice). B cell infection occurred in CTLA4-H gamma 1 transgenic mice as integrated proviral DNA could be detected in draining lymph node cells early after infection by polymerase chain reaction analysis. In mice expressing I-E, B cells were able to present the viral SAG efficiently to V beta 6+ T cells. These cells expanded specifically and were triggered to express the activation marker CD69. Further stages of progression of infection appeared to be defective. Kinetics experiments indicated that T and B cell stimulation stopped more rapidly than in control mice. B cells acquired an activated CD69+ phenotype, were induced to produce IgM but only partially switched to IgG secretion. Finally, the dissemination of infected cells to other lymph nodes and spleen was reduced and the peripheral deletion of V beta 6+ T cells was minimal. In contrast, in mice lacking I-E, T cell stimulation was also impaired and B cell activation undetectable. These data implicate B7-dependent cellular interactions for superantigenic T cell stimulation by low-affinity TCR ligands and suggest a role of B cell differentiation in viral dissemination and peripheral T cell deletion.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Pore space analysis of beech wood: The vessel network

Water transport in wood is vital for the survival of trees. With synchrotron radiation X-ray tomographic microscopy (SRXTM), it has become possible to characterize and quantify the three-dimensional (3D) network formed by vessels that are responsible for longitudinal transport. In the present study, the spatial size dependence of vessels and the organization inside single growth rings in terms of vessel-induced porosity was studied by SRXTM. Network characteristics, such as connectivity, were deduced by digital image analysis from the processed tomographic data and related to known complex network topologies.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Implementació d'un demostrador wireless: network cording i virtualització d'interfícies sense fils

El treball realitzat en aquest projecte es basa en l'implementació d'un demostrador wireless, i més específicament, en l'estudi de les tècniques network coding i virtualització. Network coding és un nou mètode de transmissió de dades que es basa en la codificació de paquets per incrementar el rendiment fins ara obtingut als mètodes de transmissió convencionals. La virtualització és una tècnica que consisteix en compartir de forma més eficient els recursos d'un sistema. En el nostre cas s'utilitzarà la virtualització per dividir una interfície sense fils en diferents usuaris virtuals transmetent i rebent dades simultàniament. L'objectiu del projecte és realitzar un seguit de proves i estudis per veure els avantatges d'aquestes dues tècniques.

Mobile termination, network externalities, and consumer expectations

We re-examine the literature on mobile termination in the presence of network externalities. Externalities arise when firms discriminate between on- and off-net calls or when subscription demand is elastic. This literature predicts that profit decreases and consumer surplus increases in termination charge in a neighborhood of termination cost. This creates a puzzle since in reality we see regulators worldwide pushing termination rates down while being opposed by network operators. We show that this puzzle is resolved when consumers' expectations are assumed passive but required to be fulfilled in equilibrium (as defined by Katz and Shapiro, AER 1985), instead of being rationally responsive to non-equilibrium prices, as assumed until now.

A numerical solver for a nonlinear Fokker-Planck equation representation of neuronal network dynamics

To describe the collective behavior of large ensembles of neurons in neuronal network, a kinetic theory description was developed in [13, 12], where a macroscopic representation of the network dynamics was directly derived from the microscopic dynamics of individual neurons, which are modeled by conductance-based, linear, integrate-and-fire point neurons. A diffusion approximation then led to a nonlinear Fokker-Planck equation for the probability density function of neuronal membrane potentials and synaptic conductances. In this work, we propose a deterministic numerical scheme for a Fokker-Planck model of an excitatory-only network. Our numerical solver allows us to obtain the time evolution of probability distribution functions, and thus, the evolution of all possible macroscopic quantities that are given by suitable moments of the probability density function. We show that this deterministic scheme is capable of capturing the bistability of stationary states observed in Monte Carlo simulations. Moreover, the transient behavior of the firing rates computed from the Fokker-Planck equation is analyzed in this bistable situation, where a bifurcation scenario, of asynchronous convergence towards stationary states, periodic synchronous solutions or damped oscillatory convergence towards stationary states, can be uncovered by increasing the strength of the excitatory coupling. Finally, the computation of moments of the probability distribution allows us to validate the applicability of a moment closure assumption used in [13] to further simplify the kinetic theory.

SYSGENET: a meeting report from a new European network for systems genetics.

The first scientific meeting of the newly established European SYSGENET network took place at the Helmholtz Centre for Infection Research (HZI) in Braunschweig, April 7-9, 2010. About 50 researchers working in the field of systems genetics using mouse genetic reference populations (GRP) participated in the meeting and exchanged their results, phenotyping approaches, and data analysis tools for studying systems genetics. In addition, the future of GRP resources and phenotyping in Europe was discussed.

Avaluació de nous algorismes per a la creació de camins entre nodes de la xarxa TOR

En este proyecto se presenta un estudio y una implementación sobre estrategias de selección de nodos de la red TOR. Para esto en una primera parte teorica se da a conocer todo lo que comportan las redes anónimas y su implementación en diferentes entornos. A continuación se estudian los requerimientos y la viabilidad del proyecto. Finalmente exponemos el diseño y desarrollo de los distintos algoritmos propuestos juntamente con las pruebas realizadas y las conclusiones a las que se ha llegado.

Technology, business models and network structure in the airline industry

Network airlines have been increasingly focusing their operations on hub airports through the exploitation of connecting traffic, allowing them to take advantage of economies of traffic density, which are unequivocal in the airline industry. Less attention has been devoted to airlines? decisions on point-to-point thin routes, which could be served using different aircraft technologies and different business models. This paper examines, both theoretically and empirically, the impact on airlines ?networks of the two major innovations in the airline industry in the last two decades: the regional jet technology and the low-cost business model. We show that, under certain circumstances, direct services on point-to-point thin routes can be viable and thus airlines may be interested in deviating passengers out of the hub.