Search results for " sequence analysis"

showing 10 items of 294 documents

Cascades of transcriptional induction during dendritic cell maturation revealed by genome-wide expression analysis.

2003

Dendritic cells (DC) are central regulators of immunity. Signal-induced maturation of DCs is assumed to be the starting point for specific immune responses. To further understand this process, we analyzed the alteration of transcript profiles along the time course of CD40 ligand-induced maturation of human myeloid DCs by Affymetrix GeneChip microarrays covering >6800 genes. Besides rediscovery of genes already described as associated with DC maturation proving reliability of the methods used, we identified clusterin as novel maturation marker. Looking across the time course, we observed synchronized kinetics of distinct functional groups of molecules whose temporal coregulation underscores …

ChemokineTime FactorsMicroarrayTranscription GeneticCell Survivalmedicine.medical_treatmentImmunoglobulinsBiochemistryMiceAntigens CDGeneticsmedicineAnimalsHumansMolecular BiologyGeneCells CulturedOligonucleotide Array Sequence AnalysisMembrane GlycoproteinsClusterinbiologyGenome HumanReverse Transcriptase Polymerase Chain ReactionGene Expression ProfilingDendritic cell3T3 CellsDendritic CellsFlow CytometryMolecular biologyCell biologyGene expression profilingCytokinebiology.proteinB7-1 AntigenRNAB7-2 AntigenDNA microarrayBiotechnologyFASEB journal : official publication of the Federation of American Societies for Experimental Biology
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Response to long-term NaHCO3-derived alkalinity in model Lotus japonicus Ecotypes Gifu B-129 and Miyakojima MG-20: transcriptomic profiling and physi…

2014

The current knowledge regarding transcriptomic changes induced by alkalinity on plants is scarce and limited to studieswhere plants were subjected to the alkaline salt for periods not longer than 48 h, so there is no information availableregarding the regulation of genes involved in the generation of a new homeostatic cellular condition after long-termalkaline stress.Lotus japonicusis a model legume broadly used to study many important physiological processes includingbiotic interactions and biotic and abiotic stresses. In the present study, we characterized phenotipically the response toalkaline stress of the most widely usedL. japonicusecotypes, Gifu B-129 and MG-20, and analyzed global t…

ChlorophyllOtras Biotecnología AgropecuariaPhysiologyApplied MicrobiologyPlant SciencePathogenesisPathology and Laboratory MedicinePlant RootsBiochemistryTranscriptomeZINCchemistry.chemical_compoundPlant MicrobiologyGene Expression Regulation PlantABIOTIC STRESSMETAL TRANSPORTERSMedicine and Health SciencesOligonucleotide Array Sequence AnalysisLOTUS JAPONICUSPlant Growth and DevelopmentMultidisciplinarybiologyEcotypePlant BiochemistryIRONQRMicrobial Growth and Development//purl.org/becyt/ford/4.4 [https]food and beveragesPlantsZincPlant PhysiologyShootHost-Pathogen InteractionsMedicineAntacidsAnatomymicroarrayPlant ShootsResearch ArticleBiotechnologyHistologyScienceIronPlant Cell BiologyLotus japonicusBiotecnología AgropecuariaalkalinityMycologyReal-Time Polymerase Chain ReactionResearch and Analysis MethodsMicrobiologyModel OrganismsIsoflavonoidSpecies SpecificityPlant and Algal ModelsBotanyAbiotic stressGene Expression ProfilingfungiOrganismsFungiBiology and Life SciencesPlant TranspirationCell Biologybiology.organism_classificationMICROARRAYSGene expression profilingSodium BicarbonatechemistryCIENCIAS AGRÍCOLASChlorophyllLotusPhysiological Processes//purl.org/becyt/ford/4 [https]Developmental BiologyPloS one
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Maternal Oct-4 is a potential key regulator of the developmental competence of mouse oocytes

2008

Abstract Background The maternal contribution of transcripts and proteins supplied to the zygote is crucial for the progression from a gametic to an embryonic control of preimplantation development. Here we compared the transcriptional profiles of two types of mouse MII oocytes, one which is developmentally competent (MIISN oocyte), the other that ceases development at the 2-cell stage (MIINSN oocyte), with the aim of identifying genes and gene expression networks whose misregulated expression would contribute to a reduced developmental competence. Results We report that: 1) the transcription factor Oct-4 is absent in MIINSN oocytes, accounting for 2) the down-regulation of Stella, a matern…

Chromosomal Proteins Non-HistoneCleavage Stage OvumRegulatorEmbryonic DevelopmentBiologyOct-4MicemedicineAnimalsCluster AnalysisGene Regulatory Networkslcsh:QH301-705.5MetaphaseOligonucleotide Array Sequence AnalysisRegulation of gene expressionGeneticsZygoteGene Expression ProfilingGene Expression Regulation DevelopmentalOocyteEmbryonic stem cellCell biologyGene expression profilingMice Inbred C57BLRepressor ProteinsRNA Messenger Storedmedicine.anatomical_structurelcsh:Biology (General)OocytesFemaleDevelopmental biologyOctamer Transcription Factor-3Developmental BiologyResearch ArticleBMC Developmental Biology
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Transcriptome and metabolome analysis of citrus fruit to elucidate puffing disorder.

2014

a b s t r a c t A systems-level analysis reveals details of molecular mechanisms underlying puffing disorder in Citrus fruit. Flavedo, albedo and juice sac tissues of normal fruits and fruits displaying symptoms of puffing disorder were studied using metabolomics at three developmental stages. Microarrays were used to compare normal and puffed fruits for each of the three tissues. A protein-protein interaction network inferred from previous work on Arabidopsis identified hub proteins whose transcripts show significant changes in expression. Glycolysis, the backbone of primary metabolism, appeared to be severely affected by the disorder, based on both transcriptomic and metabolomic results. …

CitrusPlant ScienceBiologyTranscriptomechemistry.chemical_compoundMetabolomicsPlant Growth RegulatorsArabidopsisGeneticsMetabolomeBrassinosteroidMetabolomicsProtein Interaction MapsAbscisic acidOligonucleotide Array Sequence AnalysisPlant DiseasesAlbedo breakdown Citrus Fruit disorder Metabolomics Puffing TranscriptomicsGene Expression Profilingfood and beveragesGeneral Medicinebiology.organism_classificationchemistryBiochemistryFruitGibberellinCitric acidAgronomy and Crop ScienceSignal TransductionTranscription FactorsPlant science : an international journal of experimental plant biology
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Saccharomyces cerevisiae signature genes for predicting nitrogen deficiency during alcoholic fermentation

2007

Genome-wide analysis of the wine yeast strain Saccharomyces cerevisiae PYCC4072 identified 36 genes highly expressed under conditions of low or absent nitrogen in comparison with a nitrogen-replete condition. Reverse transcription-PCR analysis for four of these transcripts with this strain and its validation with another wine yeast strain underlines the usefulness of these signature genes for predicting nitrogen deficiency and therefore the diagnosis of wine stuck/sluggish fermentations.

Ciências Agrárias::Biotecnologia Agrária e Alimentar:Biotecnologia Agrária e Alimentar [Ciências Agrárias]Saccharomyces cerevisiae ProteinsNitrogenSaccharomyces cerevisiaeGenes FungalSaccharomyces cerevisiaeEthanol fermentationBiologyApplied Microbiology and BiotechnologySaccharomycesGenètica molecular03 medical and health sciencesSaccharomycesGene Expression Regulation Fungal030304 developmental biologyOligonucleotide Array Sequence AnalysisWineGenetics0303 health sciencesScience & TechnologyEcologyModels Genetic030306 microbiologyNitrogen deficiencyReverse Transcriptase Polymerase Chain Reactionfood and beveragesbiology.organism_classificationPhysiology and BiotechnologyYeastYeast in winemakingBiochemistryAlcoholsFermentationFermentationFood ScienceBiotechnology
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SMART: Unique splitting-while-merging framework for gene clustering

2014

© 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named "splitting merging awareness tactics" (SMART), which does not require any a priori knowledge of either the number …

Clustering algorithmsMicroarrayslcsh:MedicineGene ExpressionBioinformaticscomputer.software_genreCell SignalingData MiningCluster Analysislcsh:ScienceFinite mixture modelOligonucleotide Array Sequence AnalysisPhysicsMultidisciplinarySMART frameworkConstrained clusteringCompetitive learning modelBioassays and Physiological AnalysisMultigene FamilyCanopy clustering algorithmEngineering and TechnologyData miningInformation TechnologyGenomic Signal ProcessingAlgorithmsResearch ArticleSignal TransductionComputer and Information SciencesFuzzy clusteringCorrelation clusteringResearch and Analysis MethodsClusteringMolecular GeneticsCURE data clustering algorithmGeneticsGene RegulationCluster analysista113Gene Expression Profilinglcsh:RBiology and Life SciencesComputational BiologyCell BiologyDetermining the number of clusters in a data setComputingMethodologies_PATTERNRECOGNITIONSplitting-merging awareness tactics (SMART)Signal ProcessingAffinity propagationlcsh:QGene expressionClustering frameworkcomputer
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GenClust: A genetic algorithm for clustering gene expression data

2005

Abstract Background Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering. Results GenClust is a new genetic algorithm for clustering gene expression data. It has two key features: (a) a novel coding of the search space that is simple, …

Clustering high-dimensional dataDNA ComplementaryComputer scienceRand indexCorrelation clusteringOligonucleotidesEvolutionary algorithmlcsh:Computer applications to medicine. Medical informaticscomputer.software_genreBiochemistryPattern Recognition AutomatedBiclusteringOpen Reading FramesStructural BiologyCURE data clustering algorithmConsensus clusteringGenetic algorithmCluster AnalysisCluster analysislcsh:QH301-705.5Molecular BiologyGene expression data Clustering Evolutionary algorithmsOligonucleotide Array Sequence AnalysisModels StatisticalBrown clusteringHeuristicGene Expression ProfilingApplied MathematicsComputational BiologyComputer Science Applicationslcsh:Biology (General)Gene Expression RegulationMutationlcsh:R858-859.7Data miningSequence AlignmentcomputerSoftwareAlgorithmsBMC Bioinformatics
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Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome…

2014

Background The scale and complexity of genomic data lend themselves to analysis using sophisticated mathematical techniques to yield information that can generate new hypotheses and so guide further experimental investigations. An ensemble clustering method has the ability to perform consensus clustering over the same set of genes from different microarray datasets by combining results from different clustering methods into a single consensus result. Results In this paper we have performed comprehensive analysis of forty yeast microarray datasets. One recently described Bi-CoPaM method can analyse expressions of the same set of genes from various microarray datasets while using different cl…

Co-regulation(Binarisation of consensus partition matrices) Bi-CoPaMGene Expression ProfilingStress responseGenes FungalCo-expressionGenome-wide analysisGene Expression Regulation FungalRibosome biogenesisSaccharomycetalesCluster AnalysisGene Regulatory NetworksBudding yeastRibosomesOligonucleotide Array Sequence AnalysisResearch ArticleBMC bioinformatics
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A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …

2013

Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…

Computer sciencecomputer.software_genreBiochemistrysymbols.namesakeDiscriminative modelStructural BiologyCluster AnalysisRelevance (information retrieval)Cluster analysisMolecular BiologyOligonucleotide Array Sequence AnalysisClustering discriminative ability of a distance function external validation indicesSettore INF/01 - InformaticaResearchApplied MathematicsMutual informationPearson product-moment correlation coefficientComputer Science ApplicationsHierarchical clusteringEuclidean distanceRange (mathematics)Metric (mathematics)symbolsData miningTranscriptomecomputerAlgorithmsBMC Bioinformatics
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Aneuploid IMR90 cells induced by depletion of pRB, DNMT1 and MAD2 show a common gene expression signature

2019

Chromosome segregation defects lead to aneuploidy which is a major feature of solid tumors. How diploid cells face chromosome mis-segregation and how aneuploidy is tolerated in tumor cells are not completely defined yet. Thus, an important goal of cancer genetics is to identify gene networks that underlie aneuploidy and are involved in its tolerance. To this aim, we induced aneuploidy in IMR90 human primary cells by depleting pRB, DNMT1 and MAD2 and analyzed their gene expression profiles by microarray analysis. Bioinformatic analysis revealed a common gene expression profile of IMR90 cells that became aneuploid. Gene Set Enrichment Analysis (GSEA) also revealed gene-sets/pathways that are …

DNA (Cytosine-5-)-Methyltransferase 1AneuploidyBiologyMicroarrayReal-Time Polymerase Chain ReactionRetinoblastoma ProteinCell LineRNA interferenceGene expressionProtein Interaction MappingGeneticsmedicineHumansGeneOligonucleotide Array Sequence AnalysisMicroarray analysis techniquesGene Expression ProfilingBioinformatics analysiChromosomeFibroblastsmedicine.diseaseAneuploidyGene Expression RegulationRNAiMad2 ProteinsDNMT1Cancer researchKIF4ARNA InterferenceTranscriptomeIMR90 human fibroblast
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