{"title":"Entropy of a network ensemble: definitions and applications to genomic data.","authors":"G. Menichetti, D. Remondini","doi":"10.1400/230154","DOIUrl":null,"url":null,"abstract":"In this paper we introduce the framework for the application of statistical mechanics to network theory, with a particular emphasis to the concept of entropy of network ensembles. This formalism provides novel observables and insights for the analysis of high-throughput transcriptomics data, integrated with apriori biological knowledge, embedded in-to available public databases of protein-protein interaction and cell signaling.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1400/230154","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper we introduce the framework for the application of statistical mechanics to network theory, with a particular emphasis to the concept of entropy of network ensembles. This formalism provides novel observables and insights for the analysis of high-throughput transcriptomics data, integrated with apriori biological knowledge, embedded in-to available public databases of protein-protein interaction and cell signaling.
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