Institute Calculo

Buenos Aires, Argentina

Institute Calculo

Buenos Aires, Argentina
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PubMed | University of Buenos Aires, Laboratorio Nacional Of Computacao Cientifica and Institute Calculo
Type: | Journal: Tuberculosis (Edinburgh, Scotland) | Year: 2016

Current Tuberculosis treatment is long and expensive, faces the increasing burden of MDR/XDR strains and lack of effective treatment against latent form, resulting in an urgent need of new anti-TB drugs. Key to TB biology is its capacity to fight the hosts RNOS mediated attack. RNOS are known to display a concentration dependent mycobactericidal activity, which leads to the following hypothesis if we know which proteins are targeted by RNOS and kill TB, we we might be able to inhibit them with drugs resulting in a synergistic bactericidal effect. Based on this idea, we performed an Mtb metabolic network whole proteome analysis of potential RNOS sensitive and relevant targets which includes target druggability and essentiality criteria. Our results, available at yield new potential TB targets, like I3PS, while also providing and updated view of previous proposals becoming an important tool for researchers looking for new ways of killing TB.

Zunino L.,University of the Balearic Islands | Zunino L.,CONICET | Zunino L.,National University of La Plata | Zanin M.,Autonomous University of Madrid | And 5 more authors.
Physica A: Statistical Mechanics and its Applications | Year: 2010

The complexity-entropy causality plane has been recently introduced as a powerful tool for discriminating Gaussian from non-Gaussian process and different degrees of correlations [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102]. We propose to use this representation space to distinguish the stage of stock market development. Our empirical results demonstrate that this statistical physics approach is useful, allowing a more refined classification of stock market dynamics. © 2010 Elsevier B.V. All rights reserved.

Carpi L.C.,University of Newcastle | Carpi L.C.,Federal University of Minas Gerais | Rosso O.A.,Federal University of Minas Gerais | Rosso O.A.,Institute Calculo | And 3 more authors.
Physics Letters, Section A: General, Atomic and Solid State Physics | Year: 2011

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution. © 2010 Elsevier B.V. All rights reserved.

Zunino L.,University of the Balearic Islands | Zunino L.,CONICET | Zunino L.,National University of La Plata | Soriano M.C.,University of the Balearic Islands | And 4 more authors.
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

In this paper an approach to identify delay phenomena from time series is developed. We show that it is possible to perform a reliable time delay identification by using quantifiers derived from information theory, more precisely, permutation entropy and permutation statistical complexity. These quantifiers show clear extrema when the embedding delay τ of the symbolic reconstruction matches the characteristic time delay τS of the system. Numerical data originating from a time delay system based on the well-known Mackey-Glass equations operating in the chaotic regime were used as test beds. We show that our method is straightforward to apply and robust to additive observational and dynamical noise. Moreover, we find that the identification of the time delay is even more efficient in a noise environment. Our permutation approach is also able to recover the time delay in systems with low feedback rate or high nonlinearity. © 2010 The American Physical Society.

Rosso O.A.,Federal University of Minas Gerais | Rosso O.A.,Institute Calculo | Rosso O.A.,CONICET | Carpi L.C.,Federal University of Minas Gerais | And 7 more authors.
Physica A: Statistical Mechanics and its Applications | Year: 2012

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the "causal" entropycomplexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigó, S. Zambrano, M.A.F. Sanjuán, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 20202029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r=4) to which we added correlated noise (colored noise with f-k Power Spectrum, 0≤k≤2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropycomplexity plane this goal can be achieved without additional computations. © 2011 Elsevier B.V. All rights reserved.

Soriano M.C.,University of the Balearic Islands | Zunino L.,University of the Balearic Islands | Zunino L.,CONICET | Zunino L.,National University of La Plata | And 4 more authors.
IEEE Journal of Quantum Electronics | Year: 2011

We analyze the intrinsic time scales of the chaotic dynamics of a semiconductor laser subject to optical feedback by estimating quantifiers derived from a permutation information approach. Based on numerically and experimentally obtained times series, we find that permutation entropy and permutation statistical complexity allow the extraction of important characteristics of the dynamics of the system. We provide evidence that permutation statistical complexity is complementary to permutation entropy, giving valuable insights into the role of the different time scales involved in the chaotic regime of the semiconductor laser dynamics subject to delay optical feedback. The results obtained confirm that this novel approach is a conceptually simple and computationally efficient method to identify the characteristic time scales of this relevant physical system. © 2011 IEEE.

Carpi L.C.,University of Newcastle | Saco P.M.,University of Newcastle | Rosso O.A.,Federal University of Minas Gerais | Rosso O.A.,Institute Calculo
Physica A: Statistical Mechanics and its Applications | Year: 2010

Recent research aiming at the distinction between deterministic or stochastic behavior in observational time series has looked into the properties of the "ordinal patterns" [C. Bandt, B. Pompe, Phys. Rev. Lett. 88 (2002) 174102]. In particular, new insight has been obtained considering the emergence of the so-called "forbidden ordinal patterns" [J.M. Amigó, S. Zambrano, M.A. F Sanjuán, Europhys. Lett. 79 (2007) 50001]. It was shown that deterministic one-dimensional maps always have forbidden ordinal patterns, in contrast with time series generated by an unconstrained stochastic process in which all the patterns appear with probability one. Techniques based on the comparison of this property in an observational time series and in white Gaussian noise were implemented. However, the comparison with correlated stochastic processes was not considered. In this paper we used the concept of "missing ordinal patterns" to study their decay rate as a function of the time series length in three stochastic processes with different degrees of correlation: fractional Brownian motion, fractional Gaussian noise and, noises with f- k power spectrum. We show that the decay rate of "missing ordinal patterns" in these processes depend on their correlation structures. We finally discuss the implications of the present results for the use of these properties as a tool for distinguishing deterministic from stochastic processes. © 2010 Elsevier B.V. All rights reserved.

Rosso O.A.,University of Newcastle | Rosso O.A.,Institute Calculo | De Micco L.,University of the Sea | Larrondo H.A.,University of the Sea | And 2 more authors.
International Journal of Bifurcation and Chaos | Year: 2010

A generalized Statistical Complexity Measure (SCM) is a functional that characterizes the probability distribution P associated to the time series generated by a given dynamical system. It quantifies not only randomness but also the presence of correlational structures. We review here several fundamental issues in such a respect, namely, (a) the selection of the information measure I; (b) the choice of the probability metric space and associated distance D; (c) the question of defining the so-called generalized disequilibrium Q;(d) the adequate way of picking up the probability distribution P associated to a dynamical system or time series under study, which is indeed a fundamental problem. In this communication we show (point d) that sensible improvements in the final results can be expected if the underlying probability distribution is "extracted" via appropriate consideration regarding causal effects in the system's dynamics. © World Scientific Publishing Company.

Boente G.,University of Buenos Aires | Boente G.,Institute Calculo | Rodriguez D.,University of Buenos Aires
Computational Statistics and Data Analysis | Year: 2010

In many situations, data follow a generalized partly linear model in which the mean of the responses is modeled, through a link function, linearly on some covariates and nonparametrically on the remaining ones. A new class of robust estimates for the smooth function η, associated to the nonparametric component, and for the parameter β, related to the linear one, is defined. The robust estimators are based on a three-step procedure, where large values of the deviance or Pearson residuals are bounded through a score function. These estimators allow us to make easier inferences on the regression parameter β and also improve computationally those based on a robust profile likelihood approach. The resulting estimates of β turn out to be root-n consistent and asymptotically normally distributed. Besides, the empirical influence function allows us to study the sensitivity of the estimators to anomalous observations. A robust Wald test for the regression parameter is also provided. Through a Monte Carlo study, the performance of the robust estimators and the robust Wald test is compared with that of the classical ones. © 2010 Elsevier B.V. All rights reserved.

Kelmansky D.M.,Institute Calculo
Methods in Molecular Biology | Year: 2013

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed. © Springer Science+Business Media New York 2013.

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