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Meinshausen and Buhlmann [Ann. Statist. 34 (2006) 1436–1462] showed that, for neighborhood selection in Gaussian graphical models, under a neighborhood stability condition, the LASSO is consistent, even when the number of variables is of greater order than the sample size. Zhao and Yu [(2006) J. Machine Learning Research 7 2541–2567] formalized the(More)
BACKGROUND Tumorigenic breast cancer cells that express high levels of CD44 and low or undetectable levels of CD24 (CD44(>)/CD24(>/low)) may be resistant to chemotherapy and therefore responsible for cancer relapse. These tumorigenic cancer cells can be isolated from breast cancer biopsies and propagated as mammospheres in vitro. In this study, we aimed to(More)
We study the asymptotic properties of the adaptive Lasso estimators in sparse, high-dimensional, linear regression models when the number of covariates may increase with the sample size. We consider variable selection using the adaptive Lasso, where the L1 norms in the penalty are re-weighted by data-dependent weights. We show that, if a reasonable initial(More)
WRKY-type transcription factors have multiple roles in the plant defence response and developmental processes. Their roles in the abiotic stress response remain obscure. In this study, 64 GmWRKY genes from soybean were identified, and were found to be differentially expressed under abiotic stresses. Nine GmWRKY proteins were tested for their transcription(More)
The common single-threaded execution model limits processors to exploiting only the relatively small amount of instruction-level parallelism available in application programs. The superthreaded processor, on the other hand, is a concurrent multithreaded architecture (CMA) that can exploit the multiple granularities of parallelism available in(More)
We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is "small" relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are(More)
A number of variable selection methods have been proposed involving nonconvex penalty functions. These methods, which include the smoothly clipped absolute deviation (SCAD) penalty and the minimax concave penalty (MCP), have been demonstrated to have attractive theoretical properties, but model fitting is not a straightforward task, and the resulting(More)
Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (multivariate analysis of transcript splicing), a bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the(More)
Context-aware computing is an emerging computing paradigm that can provide new or improved services by exploiting user context information. In this paper, we present a wireless-localarea-network-based (WLAN-based) indoor positioning technology. The wireless device deploys a positiondetermination model to gather location information from collected WLAN(More)
Differentiation of mesenchymal stem cells into a particular lineage is tightly regulated, and malfunction of this regulation could lead to pathological consequences. Patients with osteoporosis have increased adipocyte accumulation, but the mechanisms involved remain to be defined. In this study, we aimed to investigate if microRNAs regulate mesenchymal(More)