{"title":"微阵列基因表达及稳定规律","authors":"E. Kuruoğlu, Diego Salas, D. Ruiz","doi":"10.1109/SIU.2007.4298832","DOIUrl":null,"url":null,"abstract":"In this work, the authors study the statistical distribution of microarray gene expression data. In particular, we give a brief review of literature pointing to the non-Gaussian features of gene expression data in the form of impulsiveness and asymmetry. We note that several previous publication note the Pareto tail behaviour in the data. We present a new model, namely the stable distribution to describe the observed statistical features of the data which is a subfamily of Pareto-tail distributions.","PeriodicalId":315147,"journal":{"name":"2007 IEEE 15th Signal Processing and Communications Applications","volume":"267 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Microarray Gene Expression and Stable Laws\",\"authors\":\"E. Kuruoğlu, Diego Salas, D. Ruiz\",\"doi\":\"10.1109/SIU.2007.4298832\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, the authors study the statistical distribution of microarray gene expression data. In particular, we give a brief review of literature pointing to the non-Gaussian features of gene expression data in the form of impulsiveness and asymmetry. We note that several previous publication note the Pareto tail behaviour in the data. We present a new model, namely the stable distribution to describe the observed statistical features of the data which is a subfamily of Pareto-tail distributions.\",\"PeriodicalId\":315147,\"journal\":{\"name\":\"2007 IEEE 15th Signal Processing and Communications Applications\",\"volume\":\"267 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE 15th Signal Processing and Communications Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2007.4298832\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE 15th Signal Processing and Communications Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2007.4298832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this work, the authors study the statistical distribution of microarray gene expression data. In particular, we give a brief review of literature pointing to the non-Gaussian features of gene expression data in the form of impulsiveness and asymmetry. We note that several previous publication note the Pareto tail behaviour in the data. We present a new model, namely the stable distribution to describe the observed statistical features of the data which is a subfamily of Pareto-tail distributions.