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	A Lasso regression model for the construction of microRNA-target regulatory networks
	Lu, Yiming ; Zhou, Yang ; Qu, Wubin ; Deng, Minghua ; Zhang, Chenggang
	2011
关键词	MESSENGER-RNA LEVELS EXPRESSION CANCER METASTASIS CARCINOMA IDENTIFICATION DETERMINANTS SPECIFICITY PREDICTIONS ARGONAUTE2
英文摘要	Motivation: MicroRNAs have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Construction of miRNA-target regulatory networks can provide useful information for the study and diagnosis of complex diseases. Many sequence-based and evolutionary information-based methods have been developed to identify miRNA-mRNA targeting relationships. However, as the amount of available miRNA and gene expression data grows, a more statistical and systematic method combining sequence-based binding predictions and expression-based correlation data becomes necessary for the accurate identification of miRNA-mRNA pairs. Results: We propose a Lasso regression model for the identification of miRNA-mRNA targeting relationships that combines sequence-based prediction information, miRNA co-regulation, RISC availability and miRNA/mRNA abundance data. By comparing this modelling approach with two other known methods applied to three different datasets, we found that the Lasso regression model has considerable advantages in both sensitivity and specificity. The regression coefficients in the model can be used to determine the true regulatory efficacies in tissues and was demonstrated using the miRNA target site type data. Finally, by constructing the miRNA regulatory networks in two stages of prostate cancer (PCa), we found the several significant miRNA-hubbed network modules associated with PCa metastasis. In conclusion, the Lasso regression model is a robust and informative tool for constructing the miRNA regulatory networks for diagnosis and treatment of complex diseases.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000294067300012&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability; SCI(E); 50; ARTICLE; 17; 2406-2413; 27
语种	英语
出处	SCI
出版者	bioinformatics
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/394494]
专题	数学科学学院
推荐引用方式 GB/T 7714	Lu, Yiming,Zhou, Yang,Qu, Wubin,et al. A Lasso regression model for the construction of microRNA-target regulatory networks. 2011-01-01.

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