The Experts below are selected from a list of 115380 Experts worldwide ranked by ideXlab platform
Elisha Moses - One of the best experts on this subject based on the ideXlab platform.
-
curvature of co links uncovers hidden thematic layers in the world wide web
Proceedings of the National Academy of Sciences of the United States of America, 2002Co-Authors: Jeanpierre Eckmann, Elisha MosesAbstract:Beyond the Information stored in pages of the World Wide Web, novel types of “Meta-Information” are created when pages connect to each other. Such Meta-Information is a collective effect of independent agents writing and linking pages, hidden from the casual user. Accessing it and understanding the interrelation between connectivity and content in the World Wide Web is a challenging problem [Botafogo, R. A. & Shneiderman, B. (1991) in Proceedings of Hypertext (Assoc. Comput. Mach., New York), pp. 63–77 and Albert, R. & Barabasi, A.-L. (2002) Rev. Mod. Phys. 74, 47–97]. We demonstrate here how thematic relationships can be located precisely by looking only at the graph of hyperlinks, gleaning content and context from the Web without having to read what is in the pages. We begin by noting that reciprocal links (co-links) between pages signal a mutual recognition of authors and then focus on triangles containing such links, because triangles indicate a transitive relation. The importance of triangles is quantified by the clustering coefficient [Watts, D. J. & Strogatz, S. H. (1999) Nature (London) 393, 440–442], which we interpret as a curvature [Bridson, M. R. & Haefliger, A. (1999) Metric Spaces of Non-Positive Curvature (Springer, Berlin)]. This curvature defines a World Wide Web landscape whose connected regions of high curvature characterize a common topic. We show experimentally that reciprocity and curvature, when combined, accurately capture this Meta-Information for a wide variety of topics. As an example of future directions we analyze the neural network of Caenorhabditis elegans, using the same methods.
Udo Reichl - One of the best experts on this subject based on the ideXlab platform.
-
the Metaproteomeanalyzer a powerful open source software suite for Metaproteomics data analysis and interpretation
Journal of Proteome Research, 2015Co-Authors: Thilo Muth, Alexander Behne, Robert Heyer, Fabian Kohrs, Dirk Benndorf, Marcus Hoffmann, Miro Lehteva, Udo ReichlAbstract:The enormous challenges of mass spectrometry-based Metaproteomics are primarily related to the analysis and interpretation of the acquired data. This includes reliable identification of mass spectra and the meaningful integration of taxonomic and functional Meta-Information from samples containing hundreds of unknown species. To ease these difficulties, we developed a dedicated software suite, the MetaProteomeAnalyzer, an intuitive open-source tool for Metaproteomics data analysis and interpretation, which includes multiple search engines and the feature to decrease data redundancy by grouping protein hits to so-called Meta-proteins. We also designed a graph database back-end for the MetaProteomeAnalyzer to allow seamless analysis of results. The functionality of the MetaProteomeAnalyzer is demonstrated using a sample of a microbial community taken from a biogas plant.
Athman Bouguettaya - One of the best experts on this subject based on the ideXlab platform.
-
Social-Sensor Composition for Tapestry Scenes
IEEE Transactions on Services Computing, 2024Co-Authors: Tooba Aamir, Hai Dong, Athman BouguettayaAbstract:The extensive use of social media platforms and overwhelming amounts of imagery data creates unique opportunities for sensing, gathering and sharing Information about events. One of its potential applications is to leverage crowdsourced social media images to create a tapestry scene for scene analysis of designated locations and time intervals. The existing attempts however ignore the temporal-semantic relevance and spatio-temporal evolution of the images and direction-oriented scene reconstruction. We propose a novel social-sensor cloud (SocSen) service composition approach to form tapestry scenes for scene analysis. The novelty lies in utilising images and image Meta-Information to bypass expensive traditional image processing techniques to reconstruct scenes. Metadata, such as geolocation, time and angle of view of an image are modelled as non-functional attributes of a SocSen service. Our major contribution lies on proposing a context and direction-aware spatio-temporal clustering and recommendation approach for selecting a set of temporally and semantically similar services to compose the best available SocSen services. Analytical results based on real datasets are presented to demonstrate the performance of the proposed approach.
Xianghong Jasmine Zhou - One of the best experts on this subject based on the ideXlab platform.
-
functional annotation and network reconstruction through cross platform integration of microarray data
Nature Biotechnology, 2005Co-Authors: Xianghong Jasmine Zhou, Mingchih J Kao, Haiyan Huang, Angela M Wong, Juan Nuneziglesias, Michael Primig, Oscar M AparicioAbstract:The rapid accumulation of microarray data translates into a need for methods to effectively integrate data generated with different platforms. Here we introduce an approach, 2nd-order expression analysis, that addresses this challenge by first extracting expression patterns as Meta-Information from each data set (1st-order expression analysis) and then analyzing them across multiple data sets. Using yeast as a model system, we demonstrate two distinct advantages of our approach: we can identify genes of the same function yet without coexpression patterns and we can elucidate the cooperativities between transcription factors for regulatory network reconstruction by overcoming a key obstacle, namely the quantification of activities of transcription factors. Experiments reported in the literature and performed in our lab support a significant number of our predictions.
Jeanpierre Eckmann - One of the best experts on this subject based on the ideXlab platform.
-
curvature of co links uncovers hidden thematic layers in the world wide web
Proceedings of the National Academy of Sciences of the United States of America, 2002Co-Authors: Jeanpierre Eckmann, Elisha MosesAbstract:Beyond the Information stored in pages of the World Wide Web, novel types of “Meta-Information” are created when pages connect to each other. Such Meta-Information is a collective effect of independent agents writing and linking pages, hidden from the casual user. Accessing it and understanding the interrelation between connectivity and content in the World Wide Web is a challenging problem [Botafogo, R. A. & Shneiderman, B. (1991) in Proceedings of Hypertext (Assoc. Comput. Mach., New York), pp. 63–77 and Albert, R. & Barabasi, A.-L. (2002) Rev. Mod. Phys. 74, 47–97]. We demonstrate here how thematic relationships can be located precisely by looking only at the graph of hyperlinks, gleaning content and context from the Web without having to read what is in the pages. We begin by noting that reciprocal links (co-links) between pages signal a mutual recognition of authors and then focus on triangles containing such links, because triangles indicate a transitive relation. The importance of triangles is quantified by the clustering coefficient [Watts, D. J. & Strogatz, S. H. (1999) Nature (London) 393, 440–442], which we interpret as a curvature [Bridson, M. R. & Haefliger, A. (1999) Metric Spaces of Non-Positive Curvature (Springer, Berlin)]. This curvature defines a World Wide Web landscape whose connected regions of high curvature characterize a common topic. We show experimentally that reciprocity and curvature, when combined, accurately capture this Meta-Information for a wide variety of topics. As an example of future directions we analyze the neural network of Caenorhabditis elegans, using the same methods.
