Community Structure of the Physical Review Citation Network

We investigate the community structure of physics subfields in the citation network of all Physical Review publications between 1893 and August 2007. We focus on well-cited publications (those receiving more than 100 citations), and apply modularity maximization to uncover major communities that correspond to clearly-identifiable subfields of physics. While most of the links between communities connect those with obvious intellectual overlap, there sometimes exist unexpected connections between disparate fields due to the development of a widely-applicable theoretical technique or by cross fertilization between theory and experiment. We also examine communities decade by decade and also uncover a small number of significant links between communities that are widely separated in time.Comment: 14 pages, 7 figures, 8 tables. Version 2: various small additions in response to referee comment

A general co-expression network-based approach to gene expression analysis: comparison and applications

<p>Abstract</p> <p>Background</p> <p>Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric.</p> <p>Results</p> <p>Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression networks that are very different from that of value-based networks in the literature. Using a large set of synthetic and real microarray data, we demonstrate the superior performance of our approach over several popular existing algorithms. Applications of our approach to yeast, Arabidopsis and human cancer microarray data reveal many interesting modules, including a fatal subtype of lymphoma and a gene module regulating yeast telomere integrity, which were missed by the existing methods.</p> <p>Conclusions</p> <p>We demonstrated that our novel approach is very effective in discovering the modular structures in microarray data, both for genes and for samples. As the method is essentially parameter-free, it may be applied to large data sets where the number of clusters is difficult to estimate. The method is also very general and can be applied to other types of data. A MATLAB implementation of our algorithm can be downloaded from <url>http://cs.utsa.edu/~jruan/Software.html</url>.</p

Graph-theoretic approaches and tools for quantitatively assessing curricula coherence

In this paper, we propose a method to analyse the coherence of existing curricula at higher education institution. We focus our attention to engineering programmes at universities but the proposed method is by no means restricted to those cases. In contrast to other known methods, our approach is quantitative, decentralised, and asynchronous and allows to analyse entire programmes (in contrast to single courses) and does not depend on using specific teaching methods or tools. We propose to perform this quantitative assessment in two steps: first, representing the university programme as an opportune graph with courses and concepts as nodes and connections between courses and concepts as edges; second, analysing the structure of the programme using methods from graph theory. We thus perform two investigations, both leveraging a practical case–data collected from three engineering programmes at two Swedish universities: (a) how to represent university programmes in terms of graphs (here called concepts-courses graph (CCG)) and (b) how to reinterpret the most classical graph-theoretical node centrality indexes and connectivity and network flow results in order to analyse the programme structure, including to discover flows and mismatches

Quantitative analysis of curricula coherence using directed graphs

This paper investigates methods for quantitatively examining the connectivity and knowledge flow in a university program considering courses and concepts included in the program. The proposed method is expected to be useful to aid program design and inventory, and for communicating what concepts a course may rely on at a given point in the program. As a first step, we represent the university program as a directed graph with courses and concepts as nodes and connections between courses and concepts as directed edges. Then, we investigate the connectivity and the flow through the graph in order to gain insights into the structure of the program. We thus perform two investigations based on data collected from an engineering program at a Swedish university: a) how to represent (parts of) the university program as a graph (here called Directed Courses-Concepts Graph (DCCG)), and b) how to use graph theory tools to analyse the coherence and structure of the program

The respiratory health effects of nitrogen dioxide in children with asthma

There is growing evidence that asthma symptoms can be aggravated or events triggered by exposure to indoor nitrogen dioxide (NO2) emitted from unflued gas heating. The impact of NO2 on the respiratory health of children with asthma was explored as a secondary analysis of a randomised community trial, involving 409 households during the winter period in 2006 (June to September). Geometric mean indoor NO2 levels were 11.4 μg·m-3, while outdoor NO2 levels were 7.4 μg·m-3. Higher indoor NO2 levels (per logged unit increase) were associated with greater daily reports of lower (mean ratio 14, 95% CI 1.12-1.16) and upper respiratory tract symptoms (mean ratio 1.03, 95% CI 1.00-1.05), more frequent cough and wheeze, and more frequent reliever use during the day, but had no effect on preventer use. Higher indoor NO2 levels (per logged unit increase) were associated with a decrease in morning (-17.25 mL, 95% CI -27.63- -6.68) and evening (-13.21, 95% CI -26.03- -0.38) forced expiratory volume in 1 s readings. Outdoor NO2 was not associated with respiratory tract symptoms, asthma symptoms, medication use or lung function measurements. These findings indicate that reducing NO2 exposure indoors is important in improving the respiratory health of children with asthma. Copyright©ERS 2011