Water Cherenkov Detectors response to a Gamma Ray Burst in the Large Aperture GRB Observatory

In order to characterise the behaviour of Water Cherenkov Detectors (WCD) under a sudden increase of 1 GeV - 1 TeV background photons from a Gamma Ray Burst (GRB), simulations were conducted and compared to data acquired by the WCD of the Large Aperture GRB Observatory (LAGO). The LAGO operates arrays of WCD at high altitude to detect GRBs using the single particle technique. The LAGO sensitivity to GRBs is derived from the reported simulations of the gamma initiated particle showers in the atmosphere and the WCD response to secondaries.Comment: 5 pages, proceeding of the 31st ICRC 200

The Large Aperture GRB Observatory

The Large Aperture GRB Observatory (LAGO) is aiming at the detection of the high energy (around 100 GeV) component of Gamma Ray Bursts, using the single particle technique in arrays of Water Cherenkov Detectors (WCD) in high mountain sites (Chacaltaya, Bolivia, 5300 m a.s.l., Pico Espejo, Venezuela, 4750 m a.s.l., Sierra Negra, Mexico, 4650 m a.s.l). WCD at high altitude offer a unique possibility of detecting low gamma fluxes in the 10 GeV - 1 TeV range. The status of the Observatory and data collected from 2007 to date will be presented.Comment: 4 pages, proceeding of 31st ICRC 200

Modeling Stochasticity and Variability in Gene Regulatory Networks

Modeling stochasticity in gene regulatory networks is an important and complex problem in molecular systems biology. To elucidate intrinsic noise, several modeling strategies such as the Gillespie algorithm have been used successfully. This paper contributes an approach as an alternative to these classical settings. Within the discrete paradigm, where genes, proteins, and other molecular components of gene regulatory networks are modeled as discrete variables and are assigned as logical rules describing their regulation through interactions with other components. Stochasticity is modeled at the biological function level under the assumption that even if the expression levels of the input nodes of an update rule guarantee activation or degradation there is a probability that the process will not occur due to stochastic effects. This approach allows a finer analysis of discrete models and provides a natural setup for cell population simulations to study cell-to-cell variability. We applied our methods to two of the most studied regulatory networks, the outcome of lambda phage infection of bacteria and the p53-mdm2 complex.Comment: 23 pages, 8 figure

Control Strategy Identification via Trap Spaces in Boolean Networks

The control of biological systems presents interesting applications such as cell reprogramming or drug target identification. A common type of control strategy consists in a set of interventions that, by fixing the values of some variables, force the system to evolve to a desired state. This work presents a new approach for finding control strategies in biological systems modeled by Boolean networks. In this context, we explore the properties of trap spaces, subspaces of the state space which the dynamics cannot leave. Trap spaces for biological networks can often be efficiently computed, and provide useful approximations of attraction basins. Our approach provides control strategies for a target phenotype that are based on interventions that allow the control to be eventually released. Moreover, our method can incorporate information about the attractors to find new control strategies that would escape usual percolation-based methods. We show the applicability of our approach to two cell fate decision models.Comment: 16 pages, 2 figure

Selección participativa de nuevas variedades de papa con el diseño mamá y bebé en dos localidades de la sierra central del Perú

El objetivo del trabajo es evaluar y seleccionar participativamente genotipos promisorios de papa con resistencia a rancha (P. infestans L.), calidad culinaria y comercial (agroindustria) y con alto nivel de producción (> a 25 t/ha), así como liberar nuevas variedades con los actores de la producción, especialmente pequeños productores y con los usuarios representados por los procesadores y comercializadores mayoristas y minoristas. Se instaló dos ensayos en las localidades de 3 de Diciembre ubicado a 3,200 metros de altitud y Huancas en Jauja ubicado a 3,500 metros de altitud. La primera localidad mencionada se caracteriza por practicar un cultivo de papa primordialmente para autoconsumo y la localidad de Jauja ubicado en la zona alta de la Región, destina la producción mayormente para semilla. Los ensayos se instalaron en el mes de noviembre del 2008 y se cosecharon en el mes de abril y mayo del 2009 respectivamente

Sequential Reprogramming of Biological Network Fate

International audienceA major challenge in precision medicine consists in finding the appropriate network rewiring to induce a particular reprogramming of the cell phenotype. The rewiring is caused by specific network action either inhibiting or over-expressing targeted molecules. In some cases, a therapy abides by a time-scheduled drug administration protocol. Furthermore, some diseases are induced by a sequence of mutations leading to a sequence of actions on molecules. In this paper, we extend previous works on abductive-based inference of network reprogramming [3] by investigating the sequential control of Boolean networks. We present a novel theoretical framework and give an upper bound on the size of control sequences as a function of the number of observed variables. We also define an algorithm for inferring minimal parsimonious control sequences allowing to reach a final state satisfying a particular phenotypic property