Stochastic methods network comparison de micale giovanni (5 resultados)

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Taschenbuch. Condición: Neu. Stochastic methods for network comparison | A Gibbs sampling strategy for mining of protein-protein interaction networks and protein structures | Giovanni Micale | Taschenbuch | 112 S. | Englisch | 2018 | Edizioni Accademiche Italiane | EAN 9786202082600 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Our reality is surrounded by complex systems, characterized by entities (e.g. molecules, people, astronomical objects) with one or more associated features which interact one another (physically or virtually). Such systems are called 'complex' because they exhibit non-trivial topological features that are not observed at random, such as the tendency of entities to form communities or link to other important entities. Networks are suitable simple and general models to analyze complex systems. Network analysis, especially in a comparative framework, can reveal the existence of communities and recurrent patterns of interactions, and highlight the role of some entities and the functioning of certain processes. Data mining techniques are applied to find and extract these useful informations. However, due to the intrinsic complexity of networks, this process can be time consuming. In this book I present some novel stochastic techniques for network comparison, based on the Gibbs sampling algorithm. Although the book focuses on biological networks, the methodology presented here is domain-independent and can work on any complex system of interacting entities. 112 pp. Englisch.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Our reality is surrounded by complex systems, characterized by entities (e.g. molecules, people, astronomical objects) with one or more associated features which interact one another (physically or virtually). Such systems are called 'complex' because they exhibit non-trivial topological features that are not observed at random, such as the tendency of entities to form communities or link to other important entities. Networks are suitable simple and general models to analyze complex systems. Network analysis, especially in a comparative framework, can reveal the existence of communities and recurrent patterns of interactions, and highlight the role of some entities and the functioning of certain processes. Data mining techniques are applied to find and extract these useful informations. However, due to the intrinsic complexity of networks, this process can be time consuming. In this book I present some novel stochastic techniques for network comparison, based on the Gibbs sampling algorithm. Although the book focuses on biological networks, the methodology presented here is domain-independent and can work on any complex system of interacting entities.…

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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Micale GiovanniI was born in Catania in 1987. I took a Master Degree in Computer Science in 2011 at University of Catania and a PhD in Computer Science at University of Pisa in 2015. Now I am doing research at University of Catania. .…

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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Our reality is surrounded by complex systems, characterized by entities (e.g. molecules, people, astronomical objects) with one or more associated features which interact one another (physically or virtually). Such systems are called 'complex' because they exhibit non-trivial topological features that are not observed at random, such as the tendency of entities to form communities or link to other important entities. Networks are suitable simple and general models to analyze complex systems. Network analysis, especially in a comparative framework, can reveal the existence of communities and recurrent patterns of interactions, and highlight the role of some entities and the functioning of certain processes. Data mining techniques are applied to find and extract these useful informations. However, due to the intrinsic complexity of networks, this process can be time consuming. In this book I present some novel stochastic techniques for network comparison, based on the Gibbs sampling algorithm. Although the book focuses on biological networks, the methodology presented here is domain-independent and can work on any complex system of interacting entities.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch.…