Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Pregnancy outcome following maternal exposure to Mirtazapine: Preliminary results of a collaborative ENTIS study.

Introduction: Mirtazapine is a noradrenergic and serotonergic antidepressant mainly acting through blockade of presynaptic alpha-2 receptors. Published data on pregnancy outcome after exposure to mirtazapine are scarce. This study addresses the risk associated with exposure to mirtazapine during pregnancy. Patients (or Materials) and Methods: Multicenter (n = 11), observational prospective cohort study comparing pregnancy outcomes after exposure to mirtazapine with 2 matched control groups: exposure to any selective serotonin reuptake inhibitor (SSRI) as a diseasematched control group, and general controls with no exposure to medication known to be teratogenic or to any antidepressant. Data were collected by members of the European Network of Teratology Information Services (ENTIS) during individual risk counseling between 1995 and 2011. Standardized procedures for data collection were used in each center. Results: A total of 357 pregnant women exposed to mirtazapine at any time during pregnancy were included in the study and compared with 357 pregnancies from each control group. The rate of major birth defects between the mirtazapine and the SSRI group did not differ significantly (4.5% vs 4.2%; unadjusted odds ratio, 1.1; 95% confidence interval, 0.5-2.3, P = 0.9). A trend toward a higher rate of birth defects in the mirtazapine group compared with general controls did not reach statistical significance (4.2% vs 1.9%; OR, 2.4; 95% CI, 0.9-6.3; P = 0.08). The crude rate of spontaneous abortions did not differ significantly between the mirtazapine, the SSRI, and the general control groups (9.5% vs 10.4% vs 8.4%; P = 0.67), neither did the rate of deliveries resulting in live births (79.6% vs 84.3% in both control groups; P = 0.15). However, a higher rate of elective pregnancy-termination was observed in the mirtazapine group compared with SSRI and general controls (7.8% vs 3.4% vs 5.6%; P = 0.03). Premature birth (< 37 weeks) (10.6% vs 10.1% vs 7.5%; P = 0.38), gestational age at birth (median, 39 weeks; interquartile range (IQR), 38-40 in all groups; P = 0.29), and birth weight (median, 3320 g; IQR, 2979-3636 vs 3230 g; IQR, 2910-3629 vs 3338 g; IQR, 2967-3650; P = 0.34) did not differ significantly between the groups. Conclusion: This study did not observe a statistically significant difference in the rate of major birth defects between mirtazapine, SSRI-exposed, and nonexposed pregnancies. A slightly higher rate of birth defects was, however, observed in the mirtazapine and SSRI groups compared with the low rate of birth defects in our general controls. Overall, the pregnancy outcome after mirtazapine exposure in this study is very similar to that of the SSRI-exposed control group.

European collaborative study of early-onset bipolar disorder: Evidence for genetic heterogeneity on 2q14 according to age at onset.

Bipolar disorder has a genetic component, but the mode of inheritance remains unclear. A previous genome scan conducted in 70 European families led to detect eight regions linked to bipolar disease. Here, we present an investigation of whether the phenotypic heterogeneity of the disorder corresponds to genetic heterogeneity in these regions using additional markers and an extended sample of families. The MLS statistic was used for linkage analyses. The predivided sample test and the maximum likelihood binomial methods were used to test genetic homogeneity between early-onset bipolar type I (cut-off of 22 years) and other types of the disorder (later onset of bipolar type I and early-onset bipolar type II), using a total of 138 independent bipolar-affected sib-pairs. Analysis of the extended sample of families supports linkage in four regions (2q14, 3p14, 16p23, and 20p12) of the eight regions of linkage suggested by our previous genome scan. Heterogeneity testing revealed genetic heterogeneity between early and late-onset bipolar type I in the 2q14 region (P = 0.0001). Only the early form of the bipolar disorder but not the late form appeared to be linked to this region. This region may therefore include a genetic factor either specifically involved in the early-onset bipolar type I or only influencing the age at onset (AAO). Our findings illustrate that stratification according to AAO may be valuable for the identification of genetic vulnerability polymorphisms.

The policy-making structure of European regulatory networks and the domestic adoption of standards

European regulatory networks (ERNs) constitute the main governance instrument for the informal co-ordination of public regulation at the European Union (EU) level. They are in charge of co-ordinating national regulators and ensuring the implementation of harmonized regulatory policies across the EU, while also offering sector-specific expertise to the Commission. To this aim, ERNs develop 'best practices' and benchmarking procedures in the form of standards, norms and guidelines to be adopted in member states. In this paper, we focus on the Committee of European Securities Regulators and examine the consequences of the policy-making structure of ERNs on the domestic adoption of standards. We find that the regulators of countries with larger financial industries tend to occupy more central positions in the network, especially among newer member states. In turn, network centrality is associated with a more prompt domestic adoption of standards.

MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks.

SUMMARY: MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website's functionality. Availability and implementation: MetaNetX.org is available at http://metanetx.org. CONTACT: help@metanetx.org.

Patterns of recovery following focal hemispheric lesions : relationship between lasting deficit and damage to specialized networks

Rapport de synthèse : Objectif : Les déficits cognitifs présents dans la phase aiguë d'une lésion hémisphérique focale ont tendance à être de nature plus importante et plus générale que les déficits résiduels qui persistent dans la phase chronique de récupération. Nous avons investigué, dans le cadre de ce travail, les modèles de récupération auditive et la relation qui se dessine entre les déficits et les dommages relatifs à des réseaux spécifiques, pris comme modèle cognitif des fonctions auditives. De nombreuses études humaines dans les domaines de la neuropsychologie, de la psychophysique ainsi que des études d'activation suggèrent que les processus de reconnaissance et de localisation sonores sont effectués par l'intermédiaire de réseaux distincts tant sur le plan anatomique que fonctionnel : il s'agit des zones de traitement du «What» et du «Where », qui sont toutes deux présentes dans les deux hémisphères. Des études ont démontré que des lésions hémisphériques focales gauches ou droites, centrées sur ces réseaux, sont associées dans la phase chronique de récupération à des déficits correspondant en ce qui concerne la reconnaissance et/ou la localisation sonore. Méthode : Dans le cadre de ce travail, nous avons analysé les résultats concernant les performances auditives chez 24 patients ayant subi des lésions hémisphériques focales avec déficits secondaires dans des tâches de reconnaissance, de localisation et/ou de perception du mouvement sonore lors d'un premier testing effectué en phase aiguë (9 patients), en phase subaiguë (6 patients) ou en phase chronique précoce (9 patients). La totalité de ces patients ont bénéficié d'un second testing en phase chronique. Les observations effectuées ont servi à l'élaboration de patterns de récupération auditive. Résultats : Tous les 24 patients avaient initialement un déficit dans le domaine de la localisation et/ou de la perception du mouvement sonore. Dans la phase aiguë, ce déficit survenait sans atteinte spécifique du réseau «Where » chez presque la moitié des patients ; en revanche, cette situation n'était jamais observée chez les patients testés en phase chronique précoce. Une absence de récupération avait tendance à être associée à un dommage spécifique au réseau concerné ainsi qu'à la persistance d'un déficit au-delà de la phase aiguë. Les déficits résiduels n'étaient par ailleurs pas strictement en lien avec la taille lésionnelle ou l'étendue de l'atteinte du réseau spécifique. Conclusion : Nos résultats suggèrent que des mécanismes distincts sous-tendent la récupération et la plasticité à différentes périodes temporelles post-lésionnelles.

Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data

The geometry and connectivity of fractures exert a strong influence on the flow and transport properties of fracture networks. We present a novel approach to stochastically generate three-dimensional discrete networks of connected fractures that are conditioned to hydrological and geophysical data. A hierarchical rejection sampling algorithm is used to draw realizations from the posterior probability density function at different conditioning levels. The method is applied to a well-studied granitic formation using data acquired within two boreholes located 6 m apart. The prior models include 27 fractures with their geometry (position and orientation) bounded by information derived from single-hole ground-penetrating radar (GPR) data acquired during saline tracer tests and optical televiewer logs. Eleven cross-hole hydraulic connections between fractures in neighboring boreholes and the order in which the tracer arrives at different fractures are used for conditioning. Furthermore, the networks are conditioned to the observed relative hydraulic importance of the different hydraulic connections by numerically simulating the flow response. Among the conditioning data considered, constraints on the relative flow contributions were the most effective in determining the variability among the network realizations. Nevertheless, we find that the posterior model space is strongly determined by the imposed prior bounds. Strong prior bounds were derived from GPR measurements and helped to make the approach computationally feasible. We analyze a set of 230 posterior realizations that reproduce all data given their uncertainties assuming the same uniform transmissivity in all fractures. The posterior models provide valuable statistics on length scales and density of connected fractures, as well as their connectivity. In an additional analysis, effective transmissivity estimates of the posterior realizations indicate a strong influence of the DFN structure, in that it induces large variations of equivalent transmissivities between realizations. The transmissivity estimates agree well with previous estimates at the site based on pumping, flowmeter and temperature data.

Testing the validity of a set of diagnostic criteria for sensory neuronopathies: a francophone collaborative study.

There are no validated criteria for the diagnosis of sensory neuronopathy (SNN) yet. In a preliminary monocenter study a set of criteria relying on clinical and electrophysiological data showed good sensitivity and specificity for a diagnosis of probable SNN. The aim of this study was to test these criteria on a French multicenter study. 210 patients with sensory neuropathies from 15 francophone reference centers for neuromuscular diseases were included in the study with an expert diagnosis of non-SNN, SNN or suspected SNN according to the investigations performed in these centers. Diagnosis was obtained independently from the set of criteria to be tested. The expert diagnosis was taken as the reference against which the proposed SNN criteria were tested. The set relied on clinical and electrophysiological data easily obtainable with routine investigations. 9/61 (16.4 %) of non-SNN patients, 23/36 (63.9 %) of suspected SNN, and 102/113 (90.3 %) of SNN patients according to the expert diagnosis were classified as SNN by the criteria. The SNN criteria tested against the expert diagnosis in the SNN and non-SNN groups had 90.3 % (102/113) sensitivity, 85.2 % (52/61) specificity, 91.9 % (102/111) positive predictive value, and 82.5 % (52/63) negative predictive value. Discordance between the expert diagnosis and the SNN criteria occurred in 20 cases. After analysis of these cases, 11 could be reallocated to a correct diagnosis in accordance with the SNN criteria. The proposed criteria may be useful for the diagnosis of probable SNN in patients with sensory neuropathy. They can be reached with simple clinical and paraclinical investigations.

Modeling stochasticity and robustness in gene regulatory networks.

MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.