Search results for "DNA microarray"

showing 10 items of 99 documents

Selective phenotyping, entropy reduction, and the mastermind game.

2011

Abstract Background With the advance of genome sequencing technologies, phenotyping, rather than genotyping, is becoming the most expensive task when mapping genetic traits. The need for efficient selective phenotyping strategies, i.e. methods to select a subset of genotyped individuals for phenotyping, therefore increases. Current methods have focused either on improving the detection of causative genetic variants or their precise genomic location separately. Results Here we recognize selective phenotyping as a Bayesian model discrimination problem and introduce SPARE (Selective Phenotyping Approach by Reduction of Entropy). Unlike previous methods, SPARE can integrate the information of p…

GenotypeEntropyQuantitative Trait LociBiologyQuantitative trait locusBayesian inferenceMachine learningcomputer.software_genrelcsh:Computer applications to medicine. Medical informaticsBiochemistryBayes' theoremStructural BiologyYeastsHumansEntropy (information theory)Molecular BiologyGenotypinglcsh:QH301-705.5business.industryApplied MathematicsBayes TheoremComputer Science ApplicationsPhenotypelcsh:Biology (General)Spare partlcsh:R858-859.7Artificial intelligenceDNA microarrayEntropy reductionbusinesscomputerResearch Article
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Preparation of Biomolecule Microstructures and Microarrays by Thiol-ene Photoimmobilization

2009

A mild, fast and flexible method for photoimmobilization of biomolecules based on the light-initiated thiol-ene reaction has been developed. After investigation and optimization of various surface materials, surface chemistries and reaction parameters, microstructures and microarrays of biotin, oligonucleotides, peptides, and MUC1 tandem repeat glycopeptides were prepared with this photoimmobilization method. Furthermore, MUC1 tandem repeat glycopeptide microarrays were successfully used to probe antibodies in mouse serum obtained from vaccinated mice. Dimensions of biomolecule microstructures were shown to be freely controllable through photolithographic techniques, and features down to 5 …

LightUltraviolet RaysMicroarraysOligonucleotidesBiotinNanotechnologyCorrelated Electron Systems / High Field Magnet Laboratory (HFML)BiochemistryAntibodiesMicechemistry.chemical_compoundBiotinTandem repeatIR-72760AnimalsSulfhydryl CompoundsBiochipMolecular BiologyEne reactionchemistry.chemical_classificationthiol–ene reactionphotochemistryThiol-ene reactionOligonucleotideBiomoleculeMucin-1Organic ChemistryGlycopeptidesMicroarray AnalysisPhotochemical ProcessesImmobilized ProteinsBiochipschemistryimmobilizationMolecular MedicineDNA microarrayMETIS-273430ChemBioChem
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Global Functional Analyses of Cellular Responses to Pore-Forming Toxins

2011

Here we present the first global functional analysis of cellular responses to pore-forming toxins (PFTs). PFTs are uniquely important bacterial virulence factors, comprising the single largest class of bacterial protein toxins and being important for the pathogenesis in humans of many Gram positive and Gram negative bacteria. Their mode of action is deceptively simple, poking holes in the plasma membrane of cells. The scattered studies to date of PFT-host cell interactions indicate a handful of genes are involved in cellular defenses to PFTs. How many genes are involved in cellular defenses against PFTs and how cellular defenses are coordinated are unknown. To address these questions, we pe…

MAPK/ERK pathwayTranscription GeneticImmunology/Innate ImmunityMessengerInteractomeInfectious Diseases/Bacterial InfectionsRNA interference2.1 Biological and endogenous factorsAetiologyBiology (General)Genes HelminthCaenorhabditis elegansOligonucleotide Array Sequence AnalysisGenetics0303 health sciencesGenomebiologyReverse Transcriptase Polymerase Chain ReactionGenetics and Genomics/Functional Genomics030302 biochemistry & molecular biologyrespiratory systemCell biologyInfectious DiseasesMedical MicrobiologyRNA InterferenceSignal transductionDNA microarrayTranscriptionBiotechnologyResearch ArticleSignal TransductionPore Forming Cytotoxic ProteinsQH301-705.5Virulence FactorsMAP Kinase Signaling System1.1 Normal biological development and functioningBacterial ToxinsImmunologyMicrobiologyDNA-binding proteinCell Line03 medical and health sciencesBacterial ProteinsGeneticUnderpinning researchVirologyEscherichia coliHelminthGeneticsAnimalsHumansRNA MessengerCaenorhabditis elegansCaenorhabditis elegans ProteinsMolecular BiologyGene030304 developmental biologyGenome HelminthCell MembraneGenetics and GenomicsRC581-607biology.organism_classificationrespiratory tract diseasesTranscription Factor AP-1Emerging Infectious DiseasesGenesRNAParasitologyGeneric health relevanceRNA HelminthImmunologic diseases. AllergyPLoS Pathogens
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Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

2016

International audience; Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year fol…

Male0301 basic medicineMolecular biologyMicroarrayslcsh:MedicineGene ExpressionPolynomialsMonocytesMathematical and Statistical Techniques0302 clinical medicineLongitudinal StudiesProspective Studieslcsh:ScienceOligonucleotide Array Sequence AnalysisGeneticsPrincipal Component Analysis[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyMultidisciplinaryGenomicsReplicateMiddle AgedRegressionRNA isolationBioassays and Physiological Analysis030220 oncology & carcinogenesisPhysical SciencesPrincipal component analysisFemaleRNA hybridizationDNA microarrayTranscriptome AnalysisStatistics (Mathematics)Research ArticleAdultComputational biologyBiologyBiomolecular isolationGeneralized linear mixed model03 medical and health sciencesDeming regressionExtraction techniquesGeneticsHumansStatistical MethodsAgedQuantile normalizationMolecular probe techniquesGene Expression Profilinglcsh:RBiology and Life SciencesComputational BiologyGenome AnalysisProbe hybridizationRNA extractionResearch and analysis methodsGene expression profilingMolecular biology techniquesAlgebra030104 developmental biologyNonlinear DynamicsMultivariate Analysislcsh:QMathematics[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Poor transcript-protein correlation in the brain: negatively correlating gene products reveal neuronal polarity as a potential cause

2018

Transcription, translation, and turnover of transcripts and proteins are essential for cellular function. The contribution of those factors to protein levels is under debate, as transcript levels and cognate protein levels do not necessarily correlate due to regulation of translation and protein turnover. Here we propose neuronal polarity as a third factor that is particularly evident in the CNS, leading to considerable distances between somata and axon terminals. Consequently, transcript levels may negatively correlate with cognate protein levels in CNS regions, i.e., transcript and protein levels behave reciprocally. To test this hypothesis, we performed an integrative inter-omics study a…

Male0301 basic medicineneuronal polarityintegrative omics[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/NeurobiologyBiologynegative transcript|protein correlationProteomicsBiochemistryRats Sprague-DawleyTranscriptome03 medical and health sciencesCellular and Molecular Neurosciencetranscriptomics0302 clinical medicineproteomicsTranscription (biology)[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]AnimalsRNA MessengerGeneNeuronsProtein turnoverBrainCell PolarityProteinsRatsTransport proteinCell biology030104 developmental biologySuperior olivary complexprotein transportFemaleDNA microarray030217 neurology & neurosurgery
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Bayesian model to detect phenotype-specific genes for copy number data

2012

Abstract Background An important question in genetic studies is to determine those genetic variants, in particular CNVs, that are specific to different groups of individuals. This could help in elucidating differences in disease predisposition and response to pharmaceutical treatments. We propose a Bayesian model designed to analyze thousands of copy number variants (CNVs) where only few of them are expected to be associated with a specific phenotype. Results The model is illustrated by analyzing three major human groups belonging to HapMap data. We also show how the model can be used to determine specific CNVs related to response to treatment in patients diagnosed with ovarian cancer. The …

MaleGenotypeGene DosageHapMap ProjectBiologylcsh:Computer applications to medicine. Medical informaticsPopulation stratificationBayesian inferencePolymorphism Single NucleotideBiochemistry03 medical and health sciencesBayes' theorem0302 clinical medicineStructural BiologymedicineHumansComputer SimulationGenetic Predisposition to DiseaseGenetic TestingCopy-number variationInternational HapMap Projectlcsh:QH301-705.5Molecular Biology030304 developmental biologyGenetic testingGenetics0303 health sciencesModels StatisticalModels Geneticmedicine.diagnostic_testMethodology ArticleApplied MathematicsConfoundingBayes Theorem3. Good healthComputer Science ApplicationsPhenotypelcsh:Biology (General)030220 oncology & carcinogenesislcsh:R858-859.7FemaleDNA microarrayAlgorithmsBMC Bioinformatics
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The Choice of the Filtering Method in Microarrays Affects the Inference Regarding Dosage Compensation of the Active X-Chromosome

2011

BackgroundThe hypothesis of dosage compensation of genes of the X chromosome, supported by previous microarray studies, was recently challenged by RNA-sequencing data. It was suggested that microarray studies were biased toward an over-estimation of X-linked expression levels as a consequence of the filtering of genes below the detection threshold of microarrays.Methodology/principal findingsTo investigate this hypothesis, we used microarray expression data from circulating monocytes in 1,467 individuals. In total, 25,349 and 1,156 probes were unambiguously assigned to autosomes and the X chromosome, respectively. Globally, there was a clear shift of X-linked expressions toward lower levels…

MaleMicroarrayMicroarraysScienceGene ExpressionBiologyMonocytesGenomic ImprintingMiceX Chromosome InactivationGenes X-LinkedDosage Compensation GeneticMolecular Cell BiologyGeneticsAnimalsHumansRNA MessengerBiologyX-linked recessive inheritanceX chromosomeOligonucleotide Array Sequence AnalysisGeneticsChromosomes Human XMultidisciplinaryDosage compensationAutosomeModels GeneticChromosome BiologyGene Expression ProfilingQRComputational BiologyGenomicsGene expression profilingHEK293 CellsMedicineEpigeneticsFemaleDNA microarrayGenomic imprintingGenome Expression AnalysisResearch ArticlePLoS ONE
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Correlation between EGFR Amplification and the Expression of MicroRNA-200c in Primary Glioblastoma Multiforme

2014

Extensive infiltration of the surrounding healthy brain tissue is a critical feature in glioblastoma. Several miRNAs have been related to gliomagenesis, some of them related with the EGFR pathway. We have evaluated whole-genome miRNA expression profiling associated with different EGFR amplification patterns, studied by fluorescence in situ hybridization in tissue microarrays, of 30 cases of primary glioblastoma multiforme, whose clinicopathological and immunohistochemical features have also been analyzed. MicroRNA-200c showed a very significant difference between tumors having or not EGFR amplification. This microRNA plays an important role in epithelial-mesenchymal transition, but its impl…

Malelcsh:MedicineGene expressionGene duplicationMedicine and Health Scienceslcsh:ScienceNeurological TumorsIn Situ Hybridization FluorescenceMultidisciplinaryTissue microarraymedicine.diagnostic_testBrain NeoplasmsCancer Risk FactorsGliomaMiddle AgedCadherinsErbB ReceptorsGene Expression Regulation NeoplasticNeurologyOncologyImmunohistochemistryFemaleDNA microarrayResearch ArticleSignal TransductionEpithelial-Mesenchymal TransitionGenetic Causes of CancerBiologyYoung AdultmicroRNAmedicineGeneticsCancer GeneticsHumansEpithelial–mesenchymal transitionAgedHomeodomain Proteinslcsh:RGene AmplificationBiology and Life SciencesCancers and NeoplasmsZinc Finger E-box-Binding Homeobox 1Molecular biologySurvival AnalysisMicroRNAsTissue Array AnalysisGenetics of DiseaseCancer researchlcsh:QGlioblastomaGlioblastoma MultiformeFluorescence in situ hybridizationTranscription FactorsPLoS ONE
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A Tutorial on Computational Cluster Analysis with Applications to Pattern Discovery in Microarray Data

2008

Background Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with regard to the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures available in the literature, new ones have been recently proposed, some of them specifically for microarray data. Results We consider five such measures: Clest, Consensus (Consensus Clustering), FOM (Figure of Merit), Gap (Gap Statistics) and ME (Model Explorer), in addition to the classic WCSS (Within Cluster Sum-of-S…

Microarray analysis techniquesComputer scienceApplied Mathematicscomputer.software_genreDisease clusterClusteringComputational MathematicsComputingMethodologies_PATTERNRECOGNITIONComputational Theory and MathematicsGene chip analysisMicroarray databasesData miningDNA microarrayCluster analysiscomputerMathematics in Computer Science
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Rapid microarray-based typing of forensic SNPs

2006

The single base extension-tag array (SBE-Tag Array) method is carried out on glass slides and combines the specificity of minisequencing for SNP typing with the high throughput capacity of microarrays. Following multiplex PCR, a single tube SBE reaction is carried out, and the fluorescent labelled extension products are hybridized to the complementary DNA sequence tag (cTag) immobilized on a glass slide for locus-specific laser scan analysis. The aim is to prove and optimise the conventional microarray reaction on accuracy and efficiency for forensic applications. © 2005 Elsevier B.V. All rights reserved.

MicroarrayComplementary DNAMultiplex polymerase chain reactionGlass slideSingle-nucleotide polymorphismCTAGGeneral MedicineComputational biologyTypingBiologyDNA microarrayMolecular biologyInternational Congress Series
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