Search results for "Microarrays"

showing 10 items of 49 documents

Analysis of chronic lymphotic leukemia transcriptomic profile: differences between molecular subgroups

2009

B cell chronic lymphocytic leukemia (CLL) is a lymphoproliferative disorder with a variable clinical course. Patients with unmutated IgV(H) gene show a shorter progression-free and overall survival than patients with immunoglobulin heavy chain variable regions (IgV(H)) gene mutated. In addition, BCL6 mutations identify a subgroup of patients with high risk of progression. Gene expression was analysed in 36 early-stage patients using high-density microarrays. Around 150 genes differentially expressed were found according to IgV(H) mutations, whereas no difference was found according to BCL6 mutations. Functional profiling methods allowed us to distinguish KEGG and gene ontology terms showing…

AdultMaleCancer ResearchBCL6BiologyIgVHgenomichemic and lymphatic diseasesmedicineHumansKEGGGenemicroarraysAgedAged 80 and overRegulation of gene expressionGeneticsB-LymphocytesGene Expression ProfilingZAP70HematologyMiddle Agedmedicine.diseaseBCL6Leukemia Lymphocytic Chronic B-CellDNA-Binding ProteinsGene Expression Regulation NeoplasticGene expression profilingLeukemiaOncologyTranscriptomicHealthMutationProto-Oncogene Proteins c-bcl-6Cancer researchImmunoglobulin heavy chainFemaleImmunoglobulin Heavy ChainsCLL
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1q gain and CDT2 overexpression underlie an aggressive and highly proliferative form of Ewing sarcoma

2012

12 páginas, 6 figuras, 1 tabla.-- et al.

AdultMaleCancer ResearchCandidate geneAdolescentDNA Copy Number VariationsUbiquitin-Protein Ligasesclinical outcomeBone NeoplasmsSarcoma EwingBiologyBioinformaticsPolymorphism Single NucleotideTranscriptomeIn vivoCell Line TumorGeneticsmedicineHumansChildMolecular BiologymicroarraysAgedCell ProliferationAged 80 and overCell CycleComputational BiologyInfantNuclear ProteinsMiddle Agedmedicine.disease1q GainIn vitroChromosomes Human Pair 1Child PreschoolCancer researchImmunohistochemistryFemaleCDT2SarcomaDNA microarrayEwing sarcomaComparative genomic hybridization
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Gene expression profiling of peripheral blood mononuclear cells in endometriosis identifies genes altered in non-gynaecologic chronic inflammatory di…

2011

background: Pelvic inflammatory phenomena have been suggested as critical players in the natural history of endometriosis. However, to what extent these events could affect the systemic immunologic status remains to be clarified. Here, we compared the gene expression profile in peripheral blood mononuclear cells from endometriosis patients in the severe diseased stage with the profile after a conventional surgical treatment for removal of endometriotic lesions and adhesions.   methods: Microarray analysis included four patients suffering from severe endometriosis in which blood samples were obtained few days before the surgical intervention and again 6 months later. Real-time quantitative…

AdultPathologymedicine.medical_specialtyMicroarrayPopulationEndometriosisEndometriosisInflammationBiologyReal-Time Polymerase Chain ReactionPeripheral blood mononuclear cellMiceLeukocytesmedicineAnimalsHumansPsoriasiseducationOligonucleotide Array Sequence AnalysisInflammationOsteosarcomaeducation.field_of_studyMicroarray analysis techniquesGene Expression ProfilingRehabilitationObstetrics and Gynecologyendometriosis microarrays peripheral leukocytesMiddle Agedmedicine.diseaseGene expression profilingReal-time polymerase chain reactionReproductive MedicineCase-Control StudiesChronic DiseaseImmunologyLeukocytes MononuclearFemalemedicine.symptomHuman Reproduction
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Receptor Activator of NF-kB (RANK) Expression in Primary Tumors Associates with Bone Metastasis Occurrence in Breast Cancer Patients

2011

Background\ud Receptor activator of NFkB (RANK), its ligand (RANKL) and the decoy receptor of RANKL (osteoprotegerin, OPG) play a pivotal role in bone remodeling by regulating osteoclasts formation and activity. RANKL stimulates migration of RANK-expressing tumor cells in vitro, conversely inhibited by OPG.\ud \ud Materials and Methods\ud We examined mRNA expression levels of RANKL/RANK/OPG in a publicly available microarray dataset of 295 primary breast cancer patients. We next analyzed RANK expression by immunohistochemistry in an independent series of 93 primary breast cancer specimens and investigated a possible association with clinicopathological parameters, bone recurrence and surviv…

Anatomy and PhysiologyMicroarraysSettore MED/06 - Oncologia MedicaCancer TreatmentLigandsMetastasisBone remodelingMetastasisBasic Cancer ResearchBreast TumorsBone and Soft Tissue SarcomasNeoplasm MetastasisMusculoskeletal SystemOligonucleotide Array Sequence AnalysisMultidisciplinaryPredictive markerReceptor Activator of Nuclear Factor-kappa BQRBone metastasisMiddle AgedImmunohistochemistryGene Expression Regulation NeoplasticOncologyRANKLMedicineFemaleResearch Articlemusculoskeletal diseasesmedicine.medical_specialtyHistologyScienceBone NeoplasmsBreast NeoplasmsBiologyBreast cancerAntibody TherapySDG 3 - Good Health and Well-beingOsteoprotegerinInternal medicinemedicineHumansRNA MessengerBoneBiologyAgedBreast cancer bone metastasis RANK-RANKLRANK LigandOsteoprotegerinComputational BiologyCancers and NeoplasmsRANK Ligandmedicine.diseaseEndocrinologyCancer researchbiology.protein
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Postnatal Overfeeding Causes Early Shifts in Gene Expression in the Heart and Long-Term Alterations in Cardiometabolic and Oxidative Parameters

2013

International audience; Background: Postnatal overfeeding (OF) in rodents induces a permanent moderate increase in body weight in adulthood. However, the repercussions of postnatal OF on cardiac gene expression, cardiac metabolism and nitro-oxidative stress are less well known. Methodology/Principal Findings: Immediately after birth, litters of C57BL/6 mice were either maintained at 10 (normal-fed group, NF), or reduced to 3 in order to induce OF. At weaning, mice of both groups received a standard diet. The cardiac gene expression profile was determined at weaning and cardiac metabolism and oxidative stress were assessed at 7 months. The cardiac expression of several genes, including membe…

Blood GlucoseAnatomy and PhysiologyTime FactorsMouseMicroarrays[SDV]Life Sciences [q-bio]Myocardial InfarctionGene Expressionlcsh:Medicine030204 cardiovascular system & hematologyCardiovascularmedicine.disease_causeCardiovascular SystemMiceOvernutrition0302 clinical medicineBlood plasmaInsulinlcsh:Science2. Zero hungerRegulation of gene expression0303 health sciencesMultidisciplinaryEjection fractionVentricular RemodelingHeartAnimal ModelsReactive Nitrogen Species[SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemApelin[SDV] Life Sciences [q-bio]Body CompositionMedicineFemaleDisease SusceptibilityOxidation-ReductionResearch ArticlePhysiogenomicsmedicine.medical_specialtyDiastoleEndocrine SystemMyocardial Reperfusion InjuryBiology03 medical and health sciencesModel Organisms[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemInternal medicinemedicineAnimalsWeaningVentricular remodelingBiology030304 developmental biologyEndocrine Physiology[ SDV ] Life Sciences [q-bio]Gene Expression ProfilingMyocardiumBody Weightlcsh:RComputational Biologymedicine.diseaseOxidative StressEndocrinologyGene Expression Regulationlcsh:QOxidative stress
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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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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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Computation Cluster Validation in the Big Data Era

2017

Data-driven class discovery, i.e., the inference of cluster structure in a dataset, is a fundamental task in Data Analysis, in particular for the Life Sciences. We provide a tutorial on the most common approaches used for that task, focusing on methodologies for the prediction of the number of clusters in a dataset. Although the methods that we present are general in terms of the data for which they can be used, we offer a case study relevant for Microarray Data Analysis.

Clustering high-dimensional dataClass (computer programming)Clustering validation measureSettore INF/01 - InformaticaComputer sciencebusiness.industryBig dataInferenceMicroarrays data analysiscomputer.software_genreGap statisticTask (project management)ComputingMethodologies_PATTERNRECOGNITIONCURE data clustering algorithmConsensus clusteringHypothesis testing in statisticClustering Class Discovery in Data Algorithmsb Clustering algorithmFigure of meritConsensus clusteringData miningCluster analysisbusinesscomputer
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Inkjet printing methodologies for drug screening

2010

We show for the first time a contactless, low-cost, and rapid drug screening methodology by employing inkjet printing for molecular dispensing in a microarray format. Picoliter drops containing a model substrate (D-glucose)/ inhibitor (D-glucal) couple were accurately dispensed on a single layer consisting of the enzymatic target (glucose oxidase) covalently linked to a functionalized silicon oxide support. A simple colorimetric detection method allowed one to prove the screening capability of the microarray with the possibility to assay with high reproducibility at the single spot level. Measurements of the optical signal as a function of concentration and of time verified the occurrence a…

DrugReproducibilitybiologyInkwellStereochemistryChemistrymedia_common.quotation_subjectDrug Evaluation PreclinicalNanotechnologySubstrate (printing)Microarray AnalysisSilicon DioxideAnalytical ChemistryGlucose OxidaseSensor arraybiology.proteinColorimetryInkGlucose oxidasedrug screening inkjet printing microarrays biological surfacesEnzyme InhibitorsColorimetryInkjet printingmedia_commonSettore CHIM/02 - Chimica Fisica
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Hub-Centered Gene Network Reconstruction Using Automatic Relevance Determination

2012

Network inference deals with the reconstruction of biological networks from experimental data. A variety of different reverse engineering techniques are available; they differ in the underlying assumptions and mathematical models used. One common problem for all approaches stems from the complexity of the task, due to the combinatorial explosion of different network topologies for increasing network size. To handle this problem, constraints are frequently used, for example on the node degree, number of edges, or constraints on regulation functions between network components. We propose to exploit topological considerations in the inference of gene regulatory networks. Such systems are often…

Dynamic network analysisTranscription GeneticMicroarraysSciencePosterior probabilityGene regulatory networkBiologycomputer.software_genreBioinformaticsNetwork topology03 medical and health sciences0302 clinical medicineYeastsGeneticsComputer SimulationGene Regulatory NetworksGene NetworksBiology030304 developmental biologyRegulatory NetworksHyperparameter0303 health sciencesMultidisciplinaryModels GeneticSystems BiologyQuantitative Biology::Molecular NetworksCell CycleQRComputational BiologyBayesian networkGene Expression RegulationROC CurveMedicineData miningcomputerAlgorithms030217 neurology & neurosurgeryCombinatorial explosionBiological networkResearch ArticlePLoS ONE
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