2,916 research outputs found

    Models and Algorithms for Graph Watermarking

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    We introduce models and algorithmic foundations for graph watermarking. Our frameworks include security definitions and proofs, as well as characterizations when graph watermarking is algorithmically feasible, in spite of the fact that the general problem is NP-complete by simple reductions from the subgraph isomorphism or graph edit distance problems. In the digital watermarking of many types of files, an implicit step in the recovery of a watermark is the mapping of individual pieces of data, such as image pixels or movie frames, from one object to another. In graphs, this step corresponds to approximately matching vertices of one graph to another based on graph invariants such as vertex degree. Our approach is based on characterizing the feasibility of graph watermarking in terms of keygen, marking, and identification functions defined over graph families with known distributions. We demonstrate the strength of this approach with exemplary watermarking schemes for two random graph models, the classic Erd\H{o}s-R\'{e}nyi model and a random power-law graph model, both of which are used to model real-world networks

    Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

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    Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

    A New Approach to Analyzing Patterns of Collaboration in Co-authorship Networks - Mesoscopic Analysis and Interpretation

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    This paper focuses on methods to study patterns of collaboration in co-authorship networks at the mesoscopic level. We combine qualitative methods (participant interviews) with quantitative methods (network analysis) and demonstrate the application and value of our approach in a case study comparing three research fields in chemistry. A mesoscopic level of analysis means that in addition to the basic analytic unit of the individual researcher as node in a co-author network, we base our analysis on the observed modular structure of co-author networks. We interpret the clustering of authors into groups as bibliometric footprints of the basic collective units of knowledge production in a research specialty. We find two types of coauthor-linking patterns between author clusters that we interpret as representing two different forms of cooperative behavior, transfer-type connections due to career migrations or one-off services rendered, and stronger, dedicated inter-group collaboration. Hence the generic coauthor network of a research specialty can be understood as the overlay of two distinct types of cooperative networks between groups of authors publishing in a research specialty. We show how our analytic approach exposes field specific differences in the social organization of research.Comment: An earlier version of the paper was presented at ISSI 2009, 14-17 July, Rio de Janeiro, Brazil. Revised version accepted on 2 April 2010 for publication in Scientometrics. Removed part on node-role connectivity profile analysis after finding error in calculation and deciding to postpone analysis

    Information and Computation

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    In this chapter, concepts related to information and computation are reviewed in the context of human computation. A brief introduction to information theory and different types of computation is given. Two examples of human computation systems, online social networks and Wikipedia, are used to illustrate how these can be described and compared in terms of information and computation.Comment: 9 pages, 3 figures. Draft of a chapter to be published in Michelucci, P. (Ed.) Handbook of Human Computation, Springe

    Gene expression in BMPR2 mutation carriers with and without evidence of Pulmonary Arterial Hypertension suggests pathways relevant to disease penetrance

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    <p>Abstract</p> <p>Background</p> <p>While BMPR2 mutation strongly predisposes to pulmonary arterial hypertension (PAH), only 20% of mutation carriers develop clinical disease. This finding suggests that modifier genes contribute to FPAH clinical expression. Since modifiers are likely to be common alleles, this problem is not tractable by traditional genetic approaches. Furthermore, examination of gene expression is complicated by confounding effects attributable to drugs and the disease process itself.</p> <p>Methods</p> <p>To resolve these problems, B-cells were isolated, EBV-immortalized, and cultured from familial PAH patients with BMPR2 mutations, mutation positive but disease-free family members, and family members without mutation. This allows examination of differences in gene expression without drug or disease-related effects. These differences were assayed by Affymetrix array, with follow-up by quantitative RT-PCR and additional statistical analyses.</p> <p>Results</p> <p>By gene array, we found consistent alterations in multiple pathways with known relationship to PAH, including actin organization, immune function, calcium balance, growth, and apoptosis. Selected genes were verified by quantitative RT-PCR using a larger sample set. One of these, CYP1B1, had tenfold lower expression than control groups in female but not male PAH patients. Analysis of overrepresented gene ontology groups suggests that risk of disease correlates with alterations in pathways more strongly than with any specific gene within those pathways.</p> <p>Conclusion</p> <p>Disease status in BMPR2 mutation carriers was correlated with alterations in proliferation, GTP signaling, and stress response pathway expression. The estrogen metabolizing gene CYP1B1 is a strong candidate as a modifier gene in female PAH patients.</p

    Astrobiological Complexity with Probabilistic Cellular Automata

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    Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo
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