Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Numerical simulation of drop impact and jet buckling problems using the eXtended Pom-Pom model

This work presents numerical simulations of two fluid flow problems involving moving free surfaces: the impacting drop and fluid jet buckling. The viscoelastic model used in these simulations is the eXtended Pom-Pom (XPP) model. To validate the code, numerical predictions of the drop impact problem for Newtonian and Oldroyd-B fluids are presented and compared with other methods. In particular, a benchmark on numerical simulations for a XPP drop impacting on a rigid plate is performed for a wide range of the relevant parameters. Finally, to provide an additional application of free surface flows of XPP fluids, the viscous jet buckling problem is simulated and discussed. (C) 2011 Elsevier B.V. All rights reserved.

Computer simulation study of collective dynamics in the glass former Ca(NO3)(2)center dot 4H(2)O

Time correlation functions of current fluctuations were calculated by molecular dynamics (MD) simulations in order to investigate sound waves of high wavevectors in the glass-forming liquid Ca(NO3)(2)center dot 4H(2)O. Dispersion curves, omega(k), were obtained for longitudinal (LA) and transverse acoustic (TA) modes, and also for longitudinal optic (LO) modes. Spectra of LA modes calculated by MD simulations were modeled by a viscoelastic model within the memory function framework. The viscoelastic model is used to rationalize the change of slope taking place at k similar to 0.3 angstrom(-1) in the omega(k) curve of acoustic modes. For still larger wavevectors, mixing of acoustic and optic modes is observed. Partial time correlation functions of longitudinal mass currents were calculated separately for the ions and the water molecules. The wavevector dependence of excitation energies of the corresponding partial LA modes indicates the coexistence of a relatively stiff subsystem made of cations and anions, and a softer subsystem made of water molecules. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4751548]

Asymptotic integral kernel for ensembles of random normal matrices with radial potentials

The method of steepest descent is used to study the integral kernel of a family of normal random matrix ensembles with eigenvalue distribution P-N (z(1), ... , z(N)) = Z(N)(-1)e(-N)Sigma(N)(i=1) V-alpha(z(i)) Pi(1 <= i<j <= N) vertical bar z(i) - z(j)vertical bar(2), where V-alpha(z) = vertical bar z vertical bar(alpha), z epsilon C and alpha epsilon inverted left perpendicular0, infinity inverted right perpendicular. Asymptotic formulas with error estimate on sectors are obtained. A corollary of these expansions is a scaling limit for the n-point function in terms of the integral kernel for the classical Segal-Bargmann space. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3688293]

Diallel cross among fresh market tomato inbreeding lines

The general combining ability (GCA), specific combining ability (SCA), and heterosis were studied in a complete diallel cross among fresh market tomato breeding lines with reciprocal excluded. Fifteen genotypes (five parents and ten hybrids) were tested using a randomized complete block design, with three replications, and the experiments were conducted in Itatiba, São Paulo state, Brazil, in 2005/06. The yield components evaluated were fruit yield per plant (FP), fruit number per plant (FN), average fruit weight (FW); cluster number per plant (CN); fruit number per cluster (FC), fruit wall thickness (FT) and number of locules per fruit (NL). Fruit quality components evaluated were total soluble solids (SS); total titratable acidity (TA); SS/TA ratio, fruit length (FL); fruit width (WI); length to width ratio (FL/WI). The data for each trait was first subjected to analysis of variance. Griffing's method 2, model 1 was employed to estimate the general (GCA) and specific (SCA) combining abilities. Parental and hybrid data for each trait were used to estimate of mid-parent heterosis. For plant fruit yield, IAC-2 was the best parental line with the highest GCA followed by IAC-4 and IAC-1 lines. The hybrids IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-4 showed the highest effects of SCA. High heterotic responses were found for fruit yield and plant fruit number with values up to 49.72% and 47.19%, respectively. The best hybrids for fruit yield and plant fruit number were IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-5, for fruit yield and plant fruit number, the main yield components.

Análise do erro de previsão de vazões mensais com diferentes horizontes de previsão

Este trabalho aborda o problema de previsão para séries de vazões médias mensais, no qual denomina-se de horizonte de previsão (h), o intervalo de tempo que separa a última observação usada no ajuste do modelo de previsão e o valor futuro a ser previsto. A análise do erro de previsão é feita em função deste horizonte de previsão. Estas séries possuem um comportamento periódico na média, na variância e na função de autocorrelação. Portanto, considera-se a abordagem amplamente usada para a modelagem destas séries que consiste inicialmente em remover a periodicidade na média e na variância das séries de vazões e em seguida calcular uma série padronizada para a qual são ajustados modelos estocásticos. Neste estudo considera-se para a série padronizada os modelos autorregressivos periódicos PAR (p m). As ordens p m dos modelos ajustados para cada mês são determinadas usando os seguintes critérios: a análise clássica da função de autocorrelação parcial periódica (FACPPe); usando-se o Bayesian Information Criterion (BIC) proposto em (MecLeod, 1994); e com a análise da FACPPe proposta em (Stedinger, 2001). Os erros de previsão são calculados, na escala original da série de vazão, em função dos parâmetros dos modelos ajustados e avaliados para horizontes de previsão h variando de 1 a 12 meses. Estes erros são comparados com as estimativas das variâncias das vazões para o mês que está sendo previsto. Como resultado tem-se uma avaliação da capacidade de previsão, em meses, dos modelos ajustados para cada mês.

Enhancement of Nematic Order and Global Phase Diagram of a Lattice Model for Coupled Nematic Systems

We use an infinite-range Maier-Saupe model, with two sets of local quadrupolar variables and restricted orientations, to investigate the global phase diagram of a coupled system of two nematic subsystems. The free energy and the equations of state are exactly calculated by standard techniques of statistical mechanics. The nematic-isotropic transition temperature of system A increases with both the interaction energy among mesogens of system B, and the two-subsystem coupling J. This enhancement of the nematic phase is manifested in a global phase diagram in terms of the interaction parameters and the temperature T. We make some comments on the connections of these results with experimental findings for a system of diluted ferroelectric nanoparticles embedded in a nematic liquid-crystalline environment.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Effective carrying capacity and analytical solution of a particular case of the Richards-like two-species population dynamics model

We consider a generalized two-species population dynamic model and analytically solve it for the amensalism and commensalism ecological interactions. These two-species models can be simplified to a one-species model with a time dependent extrinsic growth factor. With a one-species model with an effective carrying capacity one is able to retrieve the steady state solutions of the previous one-species model. The equivalence obtained between the effective carrying capacity and the extrinsic growth factor is complete only for a particular case, the Gompertz model. Here we unveil important aspects of sigmoid growth curves, which are relevant to growth processes and population dynamics. (C) 2011 Elsevier B.V. All rights reserved.

URANS calculations for smooth circular cylinder flow in a wide range of Reynolds Numbers: solution verification and validation

The flow around circular smooth fixed cylinder in a large range of Reynolds numbers is considered in this paper. In order to investigate this canonical case, we perform CFD calculations and apply verification & validation (V&V) procedures to draw conclusions regarding numerical error and, afterwards, assess the modeling errors and capabilities of this (U)RANS method to solve the problem. Eight Reynolds numbers between Re = 10 and Re 5 x 10(5) will be presented with, at least, four geometrically similar grids and five discretization in time for each case (when unsteady), together with strict control of iterative and round-off errors, allowing a consistent verification analysis with uncertainty estimation. Two-dimensional RANS, steady or unsteady, laminar or turbulent calculations are performed. The original 1994 k - omega SST turbulence model by Menter is used to model turbulence. The validation procedure is performed by comparing the numerical results with an extensive set of experimental results compiled from the literature. [DOI: 10.1115/1.4007571]

Estimate of corrected values and the effect of correction for measurement error in dietary data obtained by the Food Frequency Questionnaire for Adolescents (AFFQ)

The scope of this study was to estimate calibrated values for dietary data obtained by the Food Frequency Questionnaire for Adolescents (FFQA) and illustrate the effect of this approach on food consumption data. The adolescents were assessed on two occasions, with an average interval of twelve months. In 2004, 393 adolescents participated, and 289 were then reassessed in 2005. Dietary data obtained by the FFQA were calibrated using the regression coefficients estimated from the average of two 24-hour recalls (24HR) of the subsample. The calibrated values were similar to the the 24HR reference measurement in the subsample. In 2004 and 2005 a significant difference was observed between the average consumption levels of the FFQA before and after calibration for all nutrients. With the use of calibrated data the proportion of schoolchildren who had fiber intake below the recommended level increased. Therefore, it is seen that calibrated data can be used to obtain adjusted associations due to reclassification of subjects within the predetermined categories.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

Biaxial nematic phase in the Maier-Saupe model for a mixture of discs and cylinders

We analyze the global phase diagram of a Maier-Saupe lattice model with the inclusion of shape-disordered degrees of freedom to mimic a mixture of oblate and prolate molecules (discs and cylinders). In the neighborhood of a Landau multicritical point, solutions of the statistical problem can be written as a Landau-de Gennes expansion for the free energy. If the shape-disordered degrees of freedom are quenched, we confirm the existence of a biaxial nematic structure. If orientational and disorder degrees of freedom are allowed to thermalize, this biaxial solution becomes thermodynamically unstable. Also, we use a two-temperature formalism to mimic the presence of two distinct relaxation times, and show that a slight departure from complete thermalization is enough to stabilize a biaxial nematic phase.

TWO NEW WEAK CONSTRAINT QUALIFICATIONS AND APPLICATIONS

We present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients of the active constraints preserve positive linear dependence locally. A major open question was to identify the exact set of gradients whose properties had to be preserved locally and that would still work as a CQ. This is done in the first new CQ, which we call the constant rank of the subspace component (CRSC) CQ. This new CQ also preserves many of the good properties of RCPLD, such as local stability and the validity of an error bound. We also introduce an even weaker CQ, called the constant positive generator (CPG), which can replace RCPLD in the analysis of the global convergence of algorithms. We close this work by extending convergence results of algorithms belonging to all the main classes of nonlinear optimization methods: sequential quadratic programming, augmented Lagrangians, interior point algorithms, and inexact restoration.