21 research outputs found

    Community Structure of the Physical Review Citation Network

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    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

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    <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

    Quantitative analysis of curricula coherence using directed graphs

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    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

    Graph-theoretic approaches and tools for quantitatively assessing curricula coherence

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    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

    Too dry and too cold for mould germination in New Zealand dwellings?

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    The indoor climate was investigated in 25 dwellings during the winter of 2005, in the Hutt Valley region (Greater Wellington, New Zealand). A temperature/relative humidity sensor and a fungal detector were attached to the indoor side of the external wall in the living room and in the asthmatic child's bedroom for an average period of 42 days. Germinated spores in the fungal detector were counted under a microscope. Only 2% of the Aspergillus penicillioides, 6% of the Eurotium herbariorum and 22% of the Alternaria alternata inclusions, showed germination of spores. Severe visible mould contamination was observed in only 12% of rooms studied. Consistent with these results, the measured average temperature of 16.7�C � 0.2�C and relative humidity of 63% � 1% were lower than normally considered necessary for significant mould development. To confirm these results, the experiment will be repeated in the same dwellings during the winter of 2006.fungal detectors; indoor climate; relative humidity; sensors; temperature; mould germination; New Zealand; dwellings; mould contamination.
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