An introduction to low-level analysis methods of DNA microarray data

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect.

Simbrain: A visual framework for neural network analysis and education

Simbrain is a visually-oriented framework for building and analyzing neural networks. It emphasizes the analysis of networks which control agents embedded in virtual environments, and visualization of the structures which occur in the high dimensional state spaces of these networks. The program was originally intended to facilitate analysis of representational processes in embodied agents, however it is also well suited to teaching neural networks concepts to a broader audience than is traditional for neural networks courses. Simbrain was used to teach a course at a new university, UC Merced, in its inaugural year. Experiences from the course and sample lessons are provided.

The scholarly networks of Albrecht von Haller and the Economic Society of Bern – a multi-level network analysis

Here, by the example of the transfer of cultivated plants in the context of the correspondence networks of Albrecht von Haller and the Economic Society, a multi-level network analysis is suggested. By a multi-level procedure, the chronological dynamics, the social structure, the spatial distribution and the functional networking are analyzed one after the other. These four levels of network analysis do not compete with each other but are mutually supporting. This aims at a deeper understanding of how these networks contributed to an international transfer of knowledge in the 18th century.

Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes

Environmental policy and decision-making are characterized by complex interactions between different actors and sectors. As a rule, a stakeholder analysis is performed to understand those involved, but it has been criticized for lacking quality and consistency. This lack is remedied here by a formal social network analysis that investigates collaborative and multi-level governance settings in a rigorous way. We examine the added value of combining both elements. Our case study examines infrastructure planning in the Swiss water sector. Water supply and wastewater infrastructures are planned far into the future, usually on the basis of projections of past boundary conditions. They affect many actors, including the population, and are expensive. In view of increasing future dynamics and climate change, a more participatory and long-term planning approach is required. Our specific aims are to investigate fragmentation in water infrastructure planning, to understand how actors from different decision levels and sectors are represented, and which interests they follow. We conducted 27 semi-structured interviews with local stakeholders, but also cantonal and national actors. The network analysis confirmed our hypothesis of strong fragmentation: we found little collaboration between the water supply and wastewater sector (confirming horizontal fragmentation), and few ties between local, cantonal, and national actors (confirming vertical fragmentation). Infrastructure planning is clearly dominated by engineers and local authorities. Little importance is placed on longer-term strategic objectives and integrated catchment planning, but this was perceived as more important in a second analysis going beyond typical questions of stakeholder analysis. We conclude that linking a stakeholder analysis, comprising rarely asked questions, with a rigorous social network analysis is very fruitful and generates complementary results. This combination gave us deeper insight into the socio-political-engineering world of water infrastructure planning that is of vital importance to our well-being.

How involved are they really? A comparative network analysis of the institutional drivers of local actor inclusion

Different socio-economic and environmental drivers lead local communities in mountain regions to adapt land use practices and engage in protection policies. The political system also has to develop new approaches to adapt to those drivers. Local actors are the target group of those policy approaches, and the question arises of if and how much those actors are consulted or even integrated into the design of local land use and protection policies. This article addresses this question by comparing seven different case studies in Swiss mountain regions. Through a formal social network analysis, the inclusion of local actors in collaborative policy networks is investigated and compared to the involvement of other stakeholders representing the next higher sub-national or national decisional levels. Results show that there is a significant difference (1) in how local actors are embedded compared to other stakeholders; and (2) between top-down versus bottom-up designed policy processes.

Sustainability principles put into practice: case studies of network analysis in Swiss climate change adaptation

Climate adaptation policies increasingly incorporate sustainability principles into their design and implementation. Since successful adaptation by means of adaptive capacity is recognized as being dependent upon progress toward sustainable development, policy design is increasingly characterized by the inclusion of state and non-state actors (horizontal actor integration), cross-sectoral collaboration, and inter-generational planning perspectives. Comparing four case studies in Swiss mountain regions, three located in the Upper Rhone region and one case from western Switzerland, we investigate how sustainability is put into practice. We argue that collaboration networks and sustainability perceptions matter when assessing the implementation of sustainability in local climate change adaptation. In other words, we suggest that adaptation is successful where sustainability perceptions translate into cross-sectoral integration and collaboration on the ground. Data about perceptions and network relations are assessed through surveys and treated via cluster and social network analysis.

Network Analysis Reveals Sex- and Antibiotic Resistance-Associated Antivirulence Targets in Clinical Uropathogens.

Increasing antibiotic resistance among uropathogenic Escherichia coli (UPEC) is driving interest in therapeutic targeting of nonconserved virulence factor (VF) genes. The ability to formulate efficacious combinations of antivirulence agents requires an improved understanding of how UPEC deploy these genes. To identify clinically relevant VF combinations, we applied contemporary network analysis and biclustering algorithms to VF profiles from a large, previously characterized inpatient clinical cohort. These mathematical approaches identified four stereotypical VF combinations with distinctive relationships to antibiotic resistance and patient sex that are independent of traditional phylogenetic grouping. Targeting resistance- or sex-associated VFs based upon these contemporary mathematical approaches may facilitate individualized anti-infective therapies and identify synergistic VF combinations in bacterial pathogens.

Metal content of nodules at Sea Scope stations based upon different analysis methods

Information on possible resource value of sea floor manganese nodule deposits in the eastern north Pacific has been obtained by a study of records and collections of the 1972 Sea Scope Expedition.

Comparative analysis of meta-analysis methods: when to use which?

Background: Several meta-analysis methods can be used to quantitatively combine the results of a group of experiments, including the weighted mean difference, statistical vote counting, the parametric response ratio and the non-parametric response ratio. The software engineering community has focused on the weighted mean difference method. However, other meta-analysis methods have distinct strengths, such as being able to be used when variances are not reported. There are as yet no guidelines to indicate which method is best for use in each case. Aim: Compile a set of rules that SE researchers can use to ascertain which aggregation method is best for use in the synthesis phase of a systematic review. Method: Monte Carlo simulation varying the number of experiments in the meta analyses, the number of subjects that they include, their variance and effect size. We empirically calculated the reliability and statistical power in each case Results: WMD is generally reliable if the variance is low, whereas its power depends on the effect size and number of subjects per meta-analysis; the reliability of RR is generally unaffected by changes in variance, but it does require more subjects than WMD to be powerful; NPRR is the most reliable method, but it is not very powerful; SVC behaves well when the effect size is moderate, but is less reliable with other effect sizes. Detailed tables of results are annexed. Conclusions: Before undertaking statistical aggregation in software engineering, it is worthwhile checking whether there is any appreciable difference in the reliability and power of the methods. If there is, software engineers should select the method that optimizes both parameters.

Ejercicio de Análisis de Redes con Network Analysis de ArcGIS 10.

Ejercicio de Análisis de Redes con Network Analysis de ArcGIS 10

A study of matrix analysis methods for inelastic structures. Project no. 1467, Task no. 146701, prepared under Contract no. AF 33 (657)-8717 by Massachusetts Institute of Technology, Aeroelastic and Structures Research Laboratory.

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