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Sparse low-dimensional matrix factorization methods applied to biological data with latent structure Graphical model selection in high dimensional settings: Practical methods and fundamental limits
A modified version (mBIC) of the Bayesian Information Criterion (BIC) has been previously proposed for backcross designs to locate multiple interacting quantitative trait loci. In this article, we extend the method to intercross designs. We also propose two modifications of the mBIC. First we investigate a two-stage procedure in the spirit of empirical(More)
Adding cuts based on copositive matrices, we propose to improve Lovász' bound θ on the clique number and its tightening θ introduced by McEliece, Rodemich, Rumsey, and Schrijver. Candidates for cheap and efficient copositivity cuts of this type are obtained from graphs with known clique number. The cost of recently established semidefi-nite programming(More)
MOTIVATION Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices(More)
BACKGROUND The prevalence of population-wide hypertension, obesity and dyslipidemia has not been well studied in the pasture area of Xinjiang. The present epidemiological study was performed to determine the prevalence of hypertension, obesity and dyslipidemia in minority populations from the pasture area of Xinjiang and to discuss the potential risk(More)
The prevailing method of analyzing GWAS data is still to test each marker individually, although from a statistical point of view it is quite obvious that in case of complex traits such single marker tests are not ideal. Recently several model selection approaches for GWAS have been suggested, most of them based on LASSO-type procedures. Here we will(More)