Optimized LOWESS normalization parameter selection for DNA microarray data - Wikidata - awgldk - TriplyDB

Optimized LOWESS normalization parameter selection for DNA microarray data

Optimized LOWESS normalization parameter selection for DNA microarray data

http://www.wikidata.org/entity/Q24791194

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The submergence tolerance regulator Sub1A mediates stress-responsive expression of AP2/ERF transcription factors Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists Identification and functional analysis of light-responsive unique genes and gene family members in rice Refinement of light-responsive transcript lists using rice oligonucleotide arrays: evaluation of gene-redundancy Acute and chronic plasma metabolomic and liver transcriptomic stress effects in a mouse model with features of post-traumatic stress disorder A balance of Bruton's tyrosine kinase and SHIP activation regulates B cell receptor cluster formation by controlling actin remodeling.Correction of spatial bias in oligonucleotide array data.Improved normalization of systematic biases affecting ion current measurements in label-free proteomics data.Effect of data normalization on fuzzy clustering of DNA microarray data High-sensitivity transcriptome data structure and implications for analysis and biologic interpretation.Transcriptional profiling of chickpea genes differentially regulated in response to high-salinity, cold and drought Limited functional conservation of a global regulator among related bacterial genera: Lrp in Escherichia, Proteus and Vibrio Improved ChIP-chip analysis by a mixture model approach.Nonparametric methods for the analysis of single-color pathogen microarrays.Combination of genomic approaches with functional genetic experiments reveals two modes of repression of yeast middle-phase meiosis genes Factors affecting the yield of microRNAs from laser microdissectates of formalin-fixed tissue sections.The latent membrane protein 1 (LMP1) oncogene of Epstein-Barr virus can simultaneously induce and inhibit apoptosis in B cells.MicroRNA expression profiles of whole blood in lung adenocarcinoma Normalization and missing value imputation for label-free LC-MS analysis.Computational methods and opportunities for phosphorylation network medicine Multiscale modeling of the causal functional roles of nsSNPs in a genome-wide association study: application to hypoxia.Identification of a Candidate Streptococcus pneumoniae core genome and regions of diversity correlated with invasive pneumococcal disease.Transcriptomic analysis of the effects of a fish oil enriched diet on murine brains.An integrative genomics approach to biomarker discovery in breast cancer microRNA-210 is upregulated in hypoxic cardiomyocytes through Akt- and p53-dependent pathways and exerts cytoprotective effects Integrative Analysis of Response to Tamoxifen Treatment in ER-Positive Breast Cancer Using GWAS Information and Transcription Profiling Identification of genes associated with laryngeal squamous cell carcinoma samples based on bioinformatic analysis.Young intragenic miRNAs are less coexpressed with host genes than old ones: implications of miRNA-host gene coevolution.Metabolic engineering in the -omics era: elucidating and modulating regulatory networks.Identification of MLL-fusion/MYC⊣miR-26⊣TET1 signaling circuit in MLL-rearranged leukemia.miR-146a-5p inhibits TNF-α-induced adipogenesis via targeting insulin receptor in primary porcine adipocytes.Normalization using weighted negative second order exponential error functions (NeONORM) provides robustness against asymmetries in comparative transcriptome profiles and avoids false calls.Sigma Factor Regulated Cellular Response in a Non-solvent Producing Clostridium beijerinckii Degenerated Strain: A Comparative Transcriptome Analysis.Characterization of YvcJ, a conserved P-loop-containing protein, and its implication in competence in Bacillus subtilis.Evaluation of normalization and pre-clustering issues in a novel clustering approach: global optimum search with enhanced positioning.RKIP and HMGA2 regulate breast tumor survival and metastasis through lysyl oxidase and syndecan-2.Transcriptional profiling of thymidine-producing strain recombineered from Escherichia coli BL21.Whole blood microRNA expression may not be useful for screening non-small cell lung cancer.aCGH.Spline--an R package for aCGH dye bias normalization.Lung cancer xenografting alters microRNA profile but not immunophenotype.

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P2860

Optimized LOWESS normalization parameter selection for DNA microarray data

http://www.wikidata.org/entity/Q24791194

description

2004 nî lūn-bûn

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2004 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2004 թվականի դեկտեմբերին հրատարակված գիտական հոդված

@hy

2004年の論文

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2004年論文

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2004年論文

@zh-hant

2004年論文

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2004年論文

@zh-mo

2004年論文

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2004年论文

@wuu

name

Optimized LOWESS normalization parameter selection for DNA microarray data

@ast

Optimized LOWESS normalization parameter selection for DNA microarray data

@en

Optimized LOWESS normalization parameter selection for DNA microarray data

@nl

type

label

Optimized LOWESS normalization parameter selection for DNA microarray data

@ast

Optimized LOWESS normalization parameter selection for DNA microarray data

@en

Optimized LOWESS normalization parameter selection for DNA microarray data

@nl

prefLabel

Optimized LOWESS normalization parameter selection for DNA microarray data

@ast

Optimized LOWESS normalization parameter selection for DNA microarray data

@en

Optimized LOWESS normalization parameter selection for DNA microarray data

@nl

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BMC Bioinformatics

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Optimized LOWESS normalization parameter selection for DNA microarray data

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Anna-Kaarina Järvinen

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

Henrik Edgren

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Jaakko Astola

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

John A Berger

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Sanjit K Mitra

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P2860

Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

Quantitative monitoring of gene expression patterns with a complementary DNA microarray

Microarray data normalization and transformation

Analysis of variance for gene expression microarray data

Quantitative quality control in microarray image processing and data acquisition

Unfolding of microarray data.

Microarray data quality analysis: lessons from the AFGC project. Arabidopsis Functional Genomics Consortium.

Ratio statistics of gene expression levels and applications to microarray data analysis.

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Sampsa Hautaniemi

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