Sparse canonical methods for biological data integration: application to a cross-platform study. - Wikidata - wikimedia - TriplyDB

Sparse canonical methods for biological data integration: application to a cross-platform study.

Sparse canonical methods for biological data integration: application to a cross-platform study.

http://www.wikidata.org/entity/Q33403099

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The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib Dimension reduction techniques for the integrative analysis of multi-omics data Identification of genes for complex diseases using integrated analysis of multiple types of genomic data.Visualising associations between paired 'omics' data sets Group sparse canonical correlation analysis for genomic data integration.Correspondence between fMRI and SNP data by group sparse canonical correlation analysis.SPARSE INTEGRATIVE CLUSTERING OF MULTIPLE OMICS DATA SETS.Sparse models for correlative and integrative analysis of imaging and genetic data Identification of genes associated with multiple cancers via integrative analysis.ONION: Functional Approach for Integration of Lipidomics and Transcriptomics Data.Integrative subtype discovery in glioblastoma using iCluster.Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global Populations.Extensions of sparse canonical correlation analysis with applications to genomic data Integrative analysis of gene expression and copy number alterations using canonical correlation analysis.Multivariate multi-way analysis of multi-source data.A multivariate approach to the integration of multi-omics datasets More Is Better: Recent Progress in Multi-Omics Data Integration Methods Furanoterpene Diversity and Variability in the Marine Sponge Spongia officinalis, from Untargeted LC-MS/MS Metabolomic Profiling to Furanolactam Derivatives.Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems.A comparison of methods for classifying clinical samples based on proteomics data: a case study for statistical and machine learning approaches.A flexible framework for sparse simultaneous component based data integration.Identification of genes for complex diseases by integrating multiple types of genomic data.Dementia induces correlated reductions in white matter integrity and cortical thickness: a multivariate neuroimaging study with sparse canonical correlation analysis.Understanding the relationship between cotton fiber properties and non-cellulosic cell wall polysaccharides.A novel approach for biomarker selection and the integration of repeated measures experiments from two assays.GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.The peripheral blood transcriptome reflects variations in immunity traits in swine: towards the identification of biomarkers.Patterns of brain structural connectivity differentiate normal weight from overweight subjects Early-life establishment of the swine gut microbiome and impact on host phenotypes.Comparison of the effects of five dietary fibers on mucosal transcriptional profiles, and luminal microbiota composition and SCFA concentrations in murine colon.Small RNA Transcriptome of the Oral Microbiome during Periodontitis Progression.DNA microarray integromics analysis platform.Integrative and regularized principal component analysis of multiple sources of data Identification of Commensal Species Positively Correlated with Early Stress Responses to a Compromised Mucus Barrier.The highly variable microbiota associated to intestinal mucosa correlates with growth and hypoxia resistance of sea bass, Dicentrarchus labrax, submitted to different nutritional histories.integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.A molecular classification of human mesenchymal stromal cells.Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations

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P2860

Sparse canonical methods for biological data integration: application to a cross-platform study.

http://www.wikidata.org/entity/Q33403099

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2009 nî lūn-bûn

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2009 թուականի Յունուարին հրատարակուած գիտական յօդուած

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2009 թվականի հունվարին հրատարակված գիտական հոդված

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2009年の論文

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2009年学术文章

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2009年學術文章

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BMC Bioinformatics

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Christèle Robert-Granié

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Kim-Anh Lê Cao

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Pascal G P Martin

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Philippe Besse

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P2860

Cross-platform comparison and visualisation of gene expression data using co-inertia analysis

Systematic variation in gene expression patterns in human cancer cell lines

Epithelial-mesenchymal transition: at the crossroads of development and tumor metastasis

A network-based analysis of systemic inflammation in humans

A gene expression database for the molecular pharmacology of cancer

Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data.

A sparse PLS for variable selection when integrating omics data.

Chemosensitivity prediction by transcriptional profiling

Gangliosides as therapeutic targets for cancer.

Discovering functional relationships between RNA expression and chemotherapeutic susceptibility using relevance networks.

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1471-2105-10-34

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