Structural influence of gene networks on their inference: analysis of C3NET

Background: The availability of large-scale high-throughput data possesses considerable challenges toward their functional analysis. For this reason gene network inference methods gained considerable interest. However, our current knowledge, especially about the influence of the structure of a gene network on its inference, is limited.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (similar to 25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Microstructural analysis of non-woven fabrics using scanning electron microscopy and image processing. Part 1:Development and verification of the methods

This paper reports image analysis methods that have been developed to study the microstructural changes of non-wovens made by the hydroentanglement process. The validity of the image processing techniques has been ascertained by applying them to test images with known properties. The parameters in preprocessing of the scanning electron microscope (SEM) images used in image processing have been tested and optimized. The fibre orientation distribution is estimated using fast Fourier transform (FFT) and Hough transform (HT) methods. The results obtained using these two methods are in good agreement. The HT method is more demanding in computational time compared with the Fourier transform (FT) method. However, the advantage of the HT method is that the actual orientation of the lines can be concluded directly from the result of the transform without the need for any further computation. The distribution of the length of the straight fibre segments of the fabrics is evaluated by the HT method. The effect of curl of the fibres on the result of this evaluation is shown.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

Effect of rudder angle on propeller wash velocities at a seabed

This paper deals with an experimental investigation into the velocity distribution downstream of a propeller, operating at bollard pull conditions and in the presence of a mobile sediment bed. Previous investigations either ignored the effect of a rudder in the wash or considered only its influence on an unconfined jet. The velocity profiles within the jet produced by a rotating propeller with a rudder present were measured at a mobile bed and compared to currently available predictive equations. The velocity distribution profiles in the jet, influenced by bed proximity, were found not to comply with current predictive methods. The velocity distributions measured within the jet were found to be complex and non-symmetrical. To provide a basic velocity predictive tool, a neural network analysis toolbox within Matlab was utilised and trained using the experimental data.

No or only population-specific effect of PON1 on human longevity: A comprehensive meta-analysis

Paraoxonase 1 (PON1) has been suggested as a plausible candidate gene for human longevity due to its modulation of cardiovascular disease risk, by preventing oxidation of atherogenic low-density lipoprotein. The role of the PON1 192 Q/R polymorphism has been analyzed for association with survival at old age in several populations, albeit with controversial results. To reconcile the conflicting evidence, we performed a large association study with two samples of 2357 Germans and 1025 French, respectively. We combined our results with those from seven previous studies in the largest and most comprehensive meta-analysis on PON1 192 Q/R and longevity to-date, to include a total of 9580 individuals. No significant association of PON1 192 Q/R with longevity was observed, for either R allele or carriership. This finding relied on very large sample sizes, is supported by different analysis methods and is therefore considered very robust. Moreover, we have investigated a potential interaction of PON1 192 Q/R with APOE epsilon4 using data from four populations. Whereas a significant result was found in the German sample, this could not be confirmed in the other examined groups. Our large-scale meta-analysis provided no evidence that the PON1 192 Q/R polymorphism is associated with longevity, but this does not exclude the possibility of population-specific effects due to the influence of, and interaction between, different genetic and/or environmental factors (e.g. diet).

Recovering Social Networks from Individual Attributes

One of the most important challenges of network analysis remains the scarcity of reliable information on existing connection structures. This work explores theoretical and empirical methods of inferring directed networks from nodes attributes and from functions of these attributes that are computed for connected nodes. We discuss the conditions, under which an underlying connection structure can be (probabilistically) recovered, and propose a Bayesian recovery algorithm. In an empirical application, we test the algorithm on the data from the European School Survey Project on Alcohol and Other Drugs.

The discursive turn in policy analysis and the validation of policy stories

This paper is concerned with the language of policy documents in the field of health care, and how ‘readings’ of such documents might be validated in the context of a narrative analysis. The substantive focus is on a comparative study of UK health policy documents (N=20) as produced by the various assemblies, governments and executives of England, Scotland, Wales and Northern Ireland during the period 2000-2009. Following an identification of some key characteristics of narrative structure the authors indicate how text-mining strategies allied with features of semantic and network analysis can be used to unravel the basic elements of policy stories and to facilitate the presentation of data in such a way that readers can verify the strengths (and weaknesses) of any given analysis – with regard to claims concerning, say, the presence, absence, or relative importance of key ideas and concepts. Readers can also ‘see’ how the different components of any one story might fit together, and to get a sense of what has been excluded from the narrative as well as what has been included, and thereby assess the reliability and validity of interpretations that have been placed upon the data.

Two-stage RBF network construction based on particle swarm optimization

The conventional radial basis function (RBF) network optimization methods, such as orthogonal least squares or the two-stage selection, can produce a sparse network with satisfactory generalization capability. However, the RBF width, as a nonlinear parameter in the network, is not easy to determine. In the aforementioned methods, the width is always pre-determined, either by trial-and-error, or generated randomly. Furthermore, all hidden nodes share the same RBF width. This will inevitably reduce the network performance, and more RBF centres may then be needed to meet a desired modelling specification. In this paper we investigate a new two-stage construction algorithm for RBF networks. It utilizes the particle swarm optimization method to search for the optimal RBF centres and their associated widths. Although the new method needs more computation than conventional approaches, it can greatly reduce the model size and improve model generalization performance. The effectiveness of the proposed technique is confirmed by two numerical simulation examples.

Networks for systems biology: conceptual connection of data and function

The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system. © 2012 Tripahti and Emmert-Streib.

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

BACKGROUND:

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.

Evaluating the effectiveness of community-based dementia care networks:The Dementia Care Networks' Study

Purpose: The Dementia Care Networks' Study examined the effectiveness of four community-based, not-for-profit dementia networks. The study involved assessing the relationship between the types of administrative and service-delivery exchanges that occurred among the networked agencies and the network members' perception of the effectiveness of these exchanges. Design and Methods: With the use of a case-study method, the evolution, structure, and processes of each network were documented. Social network analysis using a standardized questionnaire completed by member agencies identified patterns of administrative and clinical exchanges among networked agencies. Results: Differences were found between the four networks in terms of their perceptions of service-delivery effectiveness; perceptions of administrative effectiveness did not factor significantly. Exchanges between groups of agencies (cliques) within each of the four networks were found to be more critical than those between individual agencies within each network. Implications: Integration-measured by the types of exchanges within as opposed to across networks-differentiated the four networks studied. This research contributes to our understanding of the use of multiple measures to evaluate the inner workings of service delivery and their impact on elder health and elder health care. Copyright 2005 by The Gerontological Society of America.

Analysing partial ranks by using smoothed paired comparison methods:An investigation of value orientation in Europe

This paper introduces the paired comparison model as a suitable approach for the analysis of partially ranked data. For example, the Inglehart index, collected in international social surveys to examine shifts in post-materialistic values, generates such data on a set of attitude items. However, current analysis methods have failed to account for the complex shifts in individual item values, or to incorporate subject covariates. The paired comparison model is thus developed to allow for covariate subject effects at the individual level, and a reparameterization allows the inclusion of smooth non-linear effects of continuous covariates. The Inglehart index collected in the 1993 International Social Science Programme survey is analysed, and complex non-linear changes of item values with age, level of education and religion are identified. The model proposed provides a powerful tool for social scientists.