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Statistical Applications in Genetics and Molecular Biology|September 13, 2018
A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics dataMarie Perrot-Dockès, Céline Lévy-Leduc, Julien Chiquet, et al.
Statistical Applications in Genetics and Molecular Biology|May 12, 2019
Reproducibility of biomarker identifications from mass spectrometry proteomic data in cancer studiesYulan Liang, Adam Kelemen, Arpad Kelemen
Statistical Applications in Genetics and Molecular Biology|March 9, 2011
Exploratory analysis of multiple omics datasets using the adjusted RV coefficientClaus-Dieter Mayer, Julie Lorent, Graham W Horgan
Statistical Applications in Genetics and Molecular Biology|February 5, 2011
A three component latent class model for robust semiparametric gene discoveryMarco Alfo', Alessio Farcomeni, Luca Tardella
Statistical Applications in Genetics and Molecular Biology|February 5, 2011
Log-linear modelling of protein dipeptide structure reveals interesting patterns of side-chain-backbone interactionsKerstin Hommola, Walter R Gilks, Kanti V Mardia
Statistical Applications in Genetics and Molecular Biology|October 6, 2009
Prediction of motifs based on a repeated-measures model for integrating cross-species sequence and expression dataElizabeth A Siewert, Katerina J Kechris
Statistical Applications in Genetics and Molecular Biology|April 14, 2012
Transcriptional network inference from functional similarity and expression data: a global supervised approachJérôme Ambroise, Annie Robert, Benoit Macq, et al.
Statistical Applications in Genetics and Molecular Biology|April 14, 2012
The inheritance procedure: multiple testing of tree-structured hypothesesJelle J Goeman, Livio Finos
Statistical Applications in Genetics and Molecular Biology|April 14, 2012
A model-based analysis to infer the functional content of a gene listMichael A Newton, Qiuling He, Christina Kendziorski
Statistical Applications in Genetics and Molecular Biology|April 14, 2012
A family-based probabilistic method for capturing de novo mutations from high-throughput short-read sequencing dataReed A Cartwright, Julie Hussin, Jonathan E M Keebler, et al.
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