Inferring hidden states in Langevin dynamics on large networks: Average case performance

We present average performance results for dynamical inference problems in large networks, where a set of nodes is hidden while the time trajectories of the others are observed. Examples of this scenario can occur in signal transduction and gene regulation networks. We focus on the linear stochastic dynamics of continuous variables interacting via random Gaussian couplings of generic symmetry. We analyze the inference error, given by the variance of the posterior distribution over hidden paths, in the thermodynamic limit and as a function of the system parameters and the ratio {\alpha} between the number of hidden and observed nodes. By applying Kalman filter recursions we find that the posterior dynamics is governed by an "effective" drift that incorporates the effect of the observations. We present two approaches for characterizing the posterior variance that allow us to tackle, respectively, equilibrium and nonequilibrium dynamics. The first appeals to Random Matrix Theory and reveals average spectral properties of the inference error and typical posterior relaxation times, the second is based on dynamical functionals and yields the inference error as the solution of an algebraic equation.Comment: 20 pages, 5 figure

Fermions and Loops on Graphs. I. Loop Calculus for Determinant

This paper is the first in the series devoted to evaluation of the partition function in statistical models on graphs with loops in terms of the Berezin/fermion integrals. The paper focuses on a representation of the determinant of a square matrix in terms of a finite series, where each term corresponds to a loop on the graph. The representation is based on a fermion version of the Loop Calculus, previously introduced by the authors for graphical models with finite alphabets. Our construction contains two levels. First, we represent the determinant in terms of an integral over anti-commuting Grassman variables, with some reparametrization/gauge freedom hidden in the formulation. Second, we show that a special choice of the gauge, called BP (Bethe-Peierls or Belief Propagation) gauge, yields the desired loop representation. The set of gauge-fixing BP conditions is equivalent to the Gaussian BP equations, discussed in the past as efficient (linear scaling) heuristics for estimating the covariance of a sparse positive matrix.Comment: 11 pages, 1 figure; misprints correcte

Transcriptome pathways unique to dehydration tolerant relatives of modern wheat

Among abiotic stressors, drought is a major factor responsible for dramatic yield loss in agriculture. In order to reveal differences in global expression profiles of drought tolerant and sensitive wild emmer wheat genotypes, a previously deployed shock-like dehydration process was utilized to compare transcriptomes at two time points in root and leaf tissues using the Affymetrix GeneChip(R) Wheat Genome Array hybridization. The comparison of transcriptomes reveal several unique genes or expression patterns such as differential usage of IP(3)-dependent signal transduction pathways, ethylene- and abscisic acid (ABA)-dependent signaling, and preferential or faster induction of ABA-dependent transcription factors by the tolerant genotype that distinguish contrasting genotypes indicative of distinctive stress response pathways. The data also show that wild emmer wheat is capable of engaging known drought stress responsive mechanisms. The global comparison of transcriptomes in the absence of and after dehydration underlined the gene networks especially in root tissues that may have been lost in the selection processes generating modern bread wheats

Cranial and ventricular size following shunting or endoscopic third ventriculostomy (ETV) in infants with aqueductal stenosis: further insights from the International Infant Hydrocephalus Study (IIHS)

Purpose: The craniometrics of head circumference (HC) and ventricular size are part of the clinical assessment of infants with hydrocephalus and are often utilized in conjunction with other clinical and radiological parameters to determine the success of treatment. We aimed to assess the effect of endoscopic third ventriculostomy (ETV) and shunting on craniometric measurements during the follow-up of a cohort of infants with symptomatic triventricular hydrocephalus secondary to aqueductal stenosis. Methods: We performed a post hoc analysis of data from the International Infant Hydrocephalus Study (IIHS)—a prospective, multicenter study of infants (\u3c 24 months old) with hydrocephalus from aqueductal stenosis who were treated with either an ETV or shunt. During various stages of a 5-year follow-up period, the following craniometrics were measured: HC, HC centile, HC z-score, and frontal-occipital horn ratio (FOR). Data were compared in an analysis of covariance, adjusting for baseline variables including age at surgery and sex. Results: Of 158 enrolled patients, 115 underwent an ETV, while 43 received a shunt. Both procedures led to improvements in the mean HC centile position and z-score, a trend which continued until the 5-year assessment point. A similar trend was noted for FOR which was measured at 12 months and 3 years following initial treatment. Although the values were consistently higher for ETV compared with shunt, the differences in HC value, centile, and z-score were not significant. ETV was associated with a significantly higher FOR compared with shunting at 12 months (0.52 vs 0.44; p = 0.002) and 3 years (0.46 vs 0.38; p = 0.03) of follow-up. Conclusion: ETV and shunting led to improvements in HC centile, z-score, and FOR measurements during long-term follow-up of infants with hydrocephalus secondary to aqueductal stenosis. Head size did not significantly differ between the treatment groups during follow-up, however ventricle size was greater in those undergoing ETV when measured at 1 and 3 years following treatment

Expectation propagation for continuous time stochastic processes

We consider the inverse problem of reconstructing the posterior measure over the trajec- tories of a diffusion process from discrete time observations and continuous time constraints. We cast the problem in a Bayesian framework and derive approximations to the posterior distributions of single time marginals using variational approximate inference. We then show how the approximation can be extended to a wide class of discrete-state Markov jump pro- cesses by making use of the chemical Langevin equation. Our empirical results show that the proposed method is computationally efficient and provides good approximations for these classes of inverse problems

Two terpene synthases are responsible for the major sesquiterpenes emitted from the flowers of kiwifruit (Actinidia deliciosa)

Kiwifruit vines rely on bees for pollen transfer between spatially separated male and female individuals and require synchronized flowering to ensure pollination. Volatile terpene compounds, which are important cues for insect pollinator attraction, were studied by dynamic headspace sampling in the major green-fleshed kiwifruit (Actinidia deliciosa) cultivar ‘Hayward’ and its male pollinator ‘Chieftain’. Terpene volatile levels showed a profile dominated by the sesquiterpenes α-farnesene and germacrene D. These two compounds were emitted by all floral tissues and could be observed throughout the day, with lower levels at night. The monoterpene (E)-β-ocimene was also detected in flowers but was emitted predominantly during the day and only from petal tissue. Using a functional genomics approach, two terpene synthase (TPS) genes were isolated from a ‘Hayward’ petal EST library. Bacterial expression and transient in planta data combined with analysis by enantioselective gas chromatography revealed that one TPS produced primarily (E,E)-α-farnesene and small amounts of (E)-β-ocimene, whereas the second TPS produced primarily (+)-germacrene D. Subcellular localization using GFP fusions showed that both enzymes were localized in the cytoplasm, the site for sesquiterpene production. Real-time PCR analysis revealed that both TPS genes were expressed in the same tissues and at the same times as the corresponding floral volatiles. The results indicate that two genes can account for the major floral sesquiterpene volatiles observed in both male and female A. deliciosa flowers

Application of genomicsassisted breeding for generation of climate resilient crops: progress and prospects

CCAFS Climat

Probabilistic Model Checking for Continuous-Time Markov Chains via Sequential Bayesian Inference

Probabilistic model checking for systems with large or unbounded state space is a challenging computational problem in formal modelling and its applications. Numerical algorithms require an explicit representation of the state space, while statistical approaches require a large number of samples to estimate the desired properties with high confidence. Here, we show how model checking of time-bounded path properties can be recast exactly as a Bayesian inference problem. In this novel formulation the problem can be efficiently approximated using techniques from machine learning. Our approach is inspired by a recent result in statistical physics which derived closed form differential equations for the first-passage time distribution of stochastic processes. We show on a number of non-trivial case studies that our method achieves both high accuracy and significant computational gains compared to statistical model checking

Conserved and variable correlated mutations in the plant MADS protein network

<p>Abstract</p> <p>Background</p> <p>Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. However, not much is known about the structure of these proteins or their complexes, whereas such knowledge would be valuable for a better understanding of their function. Here, we analyze those proteins and the complexes they form using a correlated mutation approach in combination with available structural, bioinformatics and experimental data.</p> <p>Results</p> <p>Correlated mutations are affected by several types of noise, which is difficult to disentangle from the real signal. In our analysis of the MADS domain proteins, we apply for the first time a correlated mutation analysis to a family of interacting proteins. This provides a unique way to investigate the amount of signal that is present in correlated mutations because it allows direct comparison of mutations in various family members and assessing their conservation. We show that correlated mutations in general are conserved within the various family members, and if not, the variability at the respective positions is less in the proteins in which the correlated mutation does not occur. Also, intermolecular correlated mutation signals for interacting pairs of proteins display clear overlap with other bioinformatics data, which is not the case for non-interacting protein pairs, an observation which validates the intermolecular correlated mutations. Having validated the correlated mutation results, we apply them to infer the structural organization of the MADS domain proteins.</p> <p>Conclusion</p> <p>Our analysis enables understanding of the structural organization of the MADS domain proteins, including support for predicted helices based on correlated mutation patterns, and evidence for a specific interaction site in those proteins.</p