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T-ReCS: stable selection of dynamically formed groups of features with application to prediction of clinical outcomes.

, , , , and . Pacific Symposium on Biocomputing (PSB), (2014)

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A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy., , , , , , , , , and . Briefings Bioinform., (January 2023)A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data., , , , , and . BMC Bioinform., 22 (3): 524 (2021)T-ReCS: stable selection of dynamically formed groups of features with application to prediction of clinical outcomes., , , , and . Pacific Symposium on Biocomputing (PSB), (2014)CINS: Cell Interaction Network inference from Single cell expression data., , , , , , , , , and . PLoS Comput. Biol., 18 (9): 1010468 (September 2022)An R package suite for microarray meta-analysis in quality control, differentially expressed gene analysis and pathway enrichment detection., , , , , , , , , and 5 other author(s). Bioinform., 28 (19): 2534-2536 (2012)Comparison of normalization methods for CodeLink Bioarray data., , , , , and . BMC Bioinform., (2005)Correction: iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects., , , , , , , , , and 1 other author(s). BMC Bioinform., 24 (1): 394 (December 2023)T-ReCS: Stable Selection of Dynamically Formed Groups of Features with Application to Prediction of Clinical Outcomes., , , , and . Pacific Symposium on Biocomputing, page 431-442. (2015)Alignment and classification of time series gene expression in clinical studies., , and . ISMB, page 147-155. (2008)