Data integration in genetics and genomics: methods and challenges - Wikidata - awgldk - TriplyDB

Data integration in genetics and genomics: methods and challenges

Data integration in genetics and genomics: methods and challenges

http://www.wikidata.org/entity/Q28748990

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Studying Cellular Signal Transduction with OMIC Technologies Strategies for Integrated Analysis of Genetic, Epigenetic, and Gene Expression Variation in Cancer: Addressing the Challenges Methods for biological data integration: perspectives and challenges Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer Discovering MicroRNA-Regulatory Modules in Multi-Dimensional Cancer Genomic Data: A Survey of Computational Methods Multiple-platform data integration method with application to combined analysis of microarray and proteomic data Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer A New Combinatorial Optimization Approach for Integrated Feature Selection Using Different Datasets: A Prostate Cancer Transcriptomic Study Data integration in the era of omics: current and future challenges A computational procedure for functional characterization of potential marker genes from molecular data: Alzheimer's as a case study iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data.Group sparse canonical correlation analysis for genomic data integration.Correspondence between fMRI and SNP data by group sparse canonical correlation analysis.Integrative network-based Bayesian analysis of diverse genomics data Kernel-PCA data integration with enhanced interpretability.Methods of integrating data to uncover genotype-phenotype interactions.Data integration of structured and unstructured sources for assigning clinical codes to patient stays PINCAGE: probabilistic integration of cancer genomics data for perturbed gene identification and sample classification.A Bayesian integrative approach for multi-platform genomic data: A kidney cancer case study.Integrating heterogeneous high-throughput data for meta-dimensional pharmacogenomics and disease-related studies Reverse engineering biomolecular systems using -omic data: challenges, progress and opportunities.Integrative analysis of multiple diverse omics datasets by sparse group multitask regression.Advances of genomic science and systems biology in renal transplantation: a review.Latent Feature Decompositions for Integrative Analysis of Multi-Platform Genomic Data Inferring differentially expressed pathways using kernel maximum mean discrepancy-based test.Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery A network perspective on unraveling the role of TRP channels in biology and disease.Integration of gene expression and methylation to unravel biological networks in glioblastoma patients.A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure.Evaluation of hierarchical models for integrative genomic analyses.Integrative correlation: Properties and relation to canonical correlations.Molecular interaction networks for the analysis of human disease: utility, limitations, and considerations.Statistical Contributions to Bioinformatics: Design, Modeling, Structure Learning, and Integration.Combining multi-modality data for searching biomarkers in schizophrenia.Conversion of array-based single nucleotide polymorphic markers for use in targeted genotyping by sequencing in hexaploid wheat (Triticum aestivum).The big questions for biodiversity informatics

P2860

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P2860

Data integration in genetics and genomics: methods and challenges

http://www.wikidata.org/entity/Q28748990

description

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年論文

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2009年論文

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2009年論文

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2009年論文

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2009年論文

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2009年论文

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name

Data integration in genetics and genomics: methods and challenges

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Data integration in genetics and genomics: methods and challenges

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Data integration in genetics and genomics: methods and challenges

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type

label

Data integration in genetics and genomics: methods and challenges

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Data integration in genetics and genomics: methods and challenges

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Data integration in genetics and genomics: methods and challenges

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prefLabel

Data integration in genetics and genomics: methods and challenges

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Data integration in genetics and genomics: methods and challenges

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Data integration in genetics and genomics: methods and challenges

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Human Genomics and Proteomics

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Data integration in genetics and genomics: methods and challenges

@en

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Jemila S Hamid

http://www.w3.org/2001/XMLSchema#string

Joseph Beyene

http://www.w3.org/2001/XMLSchema#string

Nicole M Roslin

http://www.w3.org/2001/XMLSchema#string

Vicki Ling

http://www.w3.org/2001/XMLSchema#string

P2860

Genome-wide associations of gene expression variation in humans

Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase

Significance analysis of microarrays applied to the ionizing radiation response

Sequential tests for the detection of linkage

Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes

Multi-class cancer classification by total principal component regression (TPCR) using microarray gene expression data

Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

Combining Affymetrix microarray results.

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scholarly article

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1011538

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10.4061/2009/869093

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2009

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Celia Greenwood

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