Search results for "DNA microarray"

showing 10 items of 99 documents

Compendium of TCDD-mediated transcriptomic response datasets in mammalian model systems.

2017

Background 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is the most potent congener of the dioxin class of environmental contaminants. Exposure to TCDD causes a wide range of toxic outcomes, ranging from chloracne to acute lethality. The severity of toxicity is highly dependent on the aryl hydrocarbon receptor (AHR). Binding of TCDD to the AHR leads to changes in transcription of numerous genes. Studies evaluating the transcriptional changes brought on by TCDD may provide valuable insight into the role of the AHR in human health and disease. We therefore compiled a collection of transcriptomic datasets that can be used to aid the scientific community in better understanding the transcriptiona…

0301 basic medicineMaleTCDDPolychlorinated DibenzodioxinsBioinformaticsMicroarray datasetsAHRWhite adipose tissueBiologyWeb BrowserProteomics413 Veterinary scienceMedical and Health SciencesCell LineTranscriptome03 medical and health sciencesMice0302 clinical medicineTranscription (biology)Information and Computing SciencesmedicineGeneticsAnimalsHumansheterocyclic compoundsGeneGeneticsGene Expression ProfilingRComputational BiologyBiological SciencesAryl hydrocarbon receptormedicine.disease3. Good healthRatsChloracnestomatognathic diseases030104 developmental biologyGene Expression Regulation030220 oncology & carcinogenesisAgent Orange & Dioxinbiology.proteinEnvironmental PollutantsFemaleDNA microarrayTranscriptomeSoftwareBiotechnology
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Respiratory Tularemia: Francisella Tularensis and Microarray Probe Designing

2016

Background:Francisella tularensis(F. tularensis) is the etiological microorganism for tularemia. There are different forms of tularemia such as respiratory tularemia. Respiratory tularemia is the most severe form of tularemia with a high rate of mortality; if not treated. Therefore, traditional microbiological tools and Polymerase Chain Reaction (PCR) are not useful for a rapid, reliable, accurate, sensitive and specific diagnosis. But, DNA microarray technology does. DNA microarray technology needs to appropriate microarray probe designing.Objective:The main goal of this original article was to design suitable long oligo microarray probes for detection and identification ofF. tularensis.Me…

0301 basic medicineMicroarrayBioinformaticsIn silico030106 microbiologyComputational biologyBiologyGenomeArticlelaw.inventionTularemia03 medical and health scienceslawmedicineOligo microarrayFrancisella tularensisTularemiaPolymerase chain reactionFrancisella tularensisProbe designingGeneral Immunology and MicrobiologyDNA microarraymedicine.diseasebiology.organism_classificationDry labDNA microarrayThe Open Microbiology Journal
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Identification of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome-associated DNA methylation patterns.

2018

BackgroundMyalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex condition involving multiple organ systems and characterized by persistent/relapsing debilitating fatigue, immune dysfunction, neurological problems, and other symptoms not curable for at least 6 months. Disruption of DNA methylation patterns has been tied to various immune and neurological diseases; however, its status in ME/CFS remains uncertain. Our study aimed at identifying changes in the DNA methylation patterns that associate with ME/CFS.MethodsWe extracted genomic DNA from peripheral blood mononuclear cells from 13 ME/CFS study subjects and 12 healthy controls and measured global DNA methylation by EL…

0301 basic medicineMicroarrayMicroarraysPathology and Laboratory MedicineBiochemistryEpigenesis GeneticCohort StudiesMedicine and Health SciencesSmall nucleolar RNAsPromoter Regions GeneticFatigueAntisense RNARegulation of gene expressionMultidisciplinaryDNA methylationFatigue Syndrome ChronicQRMethylationGenomicsMiddle AgedChromatin3. Good healthNucleic acidsBioassays and Physiological AnalysisCpG siteDNA methylationMedicineEpigeneticsFemaleDNA microarrayDNA modificationChromatin modificationResearch ArticleChromosome biologymusculoskeletal diseasesCell biologyScienceBiologyResearch and Analysis Methods03 medical and health sciencesSigns and SymptomsGenomic MedicineDiagnostic MedicineChronic fatigue syndromemedicineGeneticsHumansGene RegulationEpigeneticsNon-coding RNABiology and life sciencesDNAmedicine.diseaseMicroarray Analysis030104 developmental biologyImmunologyRNACpG IslandsGene expressionPLoS ONE
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Common genes associated with antidepressant response in mouse and man identify key role of glucocorticoid receptor sensitivity.

2017

Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatmen…

0301 basic medicineMicroarraysPhysiologyGene ExpressionBioinformaticsBiochemistryBiomarkers PharmacologicalTranscriptomeMice0302 clinical medicineGlucocorticoid receptorMedicine and Health SciencesBiology (General)DepressionGeneral NeuroscienceBrainDrugsAntidepressantsPhenotypeAntidepressive Agents3. Good healthBody FluidsParoxetineBioassays and Physiological AnalysisBloodMice Inbred DBAMultigene FamilyMajor depressive disorderAntidepressantDNA microarrayAnatomyGeneral Agricultural and Biological SciencesResearch ArticleQH301-705.5Antidepressant drug therapy ; Blood ; Gene regulation ; Biomarkers ; Depression ; Gene expression ; Microarrays ; AntidepressantsBiologyResearch and Analysis MethodsGeneral Biochemistry Genetics and Molecular BiologyBlood Plasma03 medical and health sciencesReceptors GlucocorticoidMental Health and PsychiatrymedicineGeneticsAnimalsHumansGene RegulationPharmacologyDepressive Disorder MajorGeneral Immunology and MicrobiologyMechanism (biology)Mood DisordersGene Expression ProfilingBiology and Life Sciencesmedicine.diseaseGene expression profiling030104 developmental biologyGene Expression RegulationCorticosterone030217 neurology & neurosurgeryBiomarkersPLoS biology
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Automated selection of homologs to track the evolutionary history of proteins

2018

Background The selection of distant homologs of a query protein under study is a usual and useful application of protein sequence databases. Such sets of homologs are often applied to investigate the function of a protein and the degree to which experimental results can be transferred from one organism to another. In particular, a variety of databases facilitates static browsing for orthologs. However, these resources have a limited power when identifying orthologs between taxonomically distant species. In addition, in some situations, for a given query protein, it is advantageous to compare the sets of orthologs from different specific organisms: this recursive step-wise search might give …

0301 basic medicineProteomeComputer scienceComputational biologyWeb toollcsh:Computer applications to medicine. Medical informaticsBiochemistryHomology (biology)Evolution Molecular03 medical and health sciences0302 clinical medicineProtein sequencingStructural BiologyHomologous chromosomeHumansDatabases ProteinMolecular Biologylcsh:QH301-705.5OrganismProtein functionMethodology ArticleApplied MathematicsProteinsA proteinComputer Science ApplicationsHomologyEvolutionary path030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONlcsh:Biology (General)Proteomelcsh:R858-859.7DNA microarraySoftware030217 neurology & neurosurgeryBMC Bioinformatics
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Accelerating metagenomic read classification on CUDA-enabled GPUs.

2016

Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed. We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced k-mers (…

0301 basic medicineTheoretical computer scienceWorkstationGPUsComputer scienceContext (language use)CUDAParallel computingBiochemistryGenomelaw.invention03 medical and health sciencesCUDAUser-Computer Interface0302 clinical medicineStructural BiologylawTaxonomic assignmentHumansMicrobiomeMolecular BiologyInternetXeonApplied MathematicsHigh-Throughput Nucleotide SequencingSequence Analysis DNAExact k-mer matchingComputer Science Applications030104 developmental biologyTitan (supercomputer)Metagenomics030220 oncology & carcinogenesisMetagenomicsDNA microarraySoftwareBMC bioinformatics
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Deep learning models for bacteria taxonomic classification of metagenomic data.

2018

Background An open challenge in translational bioinformatics is the analysis of sequenced metagenomes from various environmental samples. Of course, several studies demonstrated the 16S ribosomal RNA could be considered as a barcode for bacteria classification at the genus level, but till now it is hard to identify the correct composition of metagenomic data from RNA-seq short-read data. 16S short-read data are generated using two next generation sequencing technologies, i.e. whole genome shotgun (WGS) and amplicon (AMP); typically, the former is filtered to obtain short-reads belonging to a 16S shotgun (SG), whereas the latter take into account only some specific 16S hypervariable regions.…

0301 basic medicineTime FactorsDBNComputer scienceBiochemistryStructural BiologyRNA Ribosomal 16SDatabases Geneticlcsh:QH301-705.5Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionibiologySettore INF/01 - InformaticaShotgun sequencingApplied MathematicsAmpliconClassificationComputer Science Applicationslcsh:R858-859.7DNA microarrayShotgunAlgorithmsCNN030106 microbiologyk-mer representationlcsh:Computer applications to medicine. Medical informaticsDNA sequencing03 medical and health sciencesMetagenomicDeep LearningMolecular BiologyBacteriaModels GeneticPhylumbusiness.industryDeep learningResearchReproducibility of ResultsPattern recognitionBiological classification16S ribosomal RNAbiology.organism_classificationAmpliconHypervariable region030104 developmental biologyTaxonlcsh:Biology (General)MetagenomicsMetagenomeArtificial intelligenceMetagenomicsNeural Networks ComputerbusinessClassifier (UML)BacteriaBMC bioinformatics
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In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment

2016

Abstract: An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expre…

0301 basic medicineUterine Cervical NeoplasmMAPK3Uterine Cervical NeoplasmsBioinformaticsHeLa CellMitogen-Activated Protein Kinase0302 clinical medicineTransforming Growth Factor betaMedicineOligonucleotide Array Sequence AnalysisCancerCervical cancerABLCell CycleIn silico pathway analysiCell cycleGene Expression Regulation NeoplasticOncology030220 oncology & carcinogenesisFemaleDNA microarrayMitogen-Activated Protein KinasesTreatment targetResearch PaperHumanin silico pathway analysisMAP Kinase Signaling SystemIn silicoComputational biologytreatment targetsProto-Oncogene Proteins c-myc03 medical and health sciencesCell Line TumorBiomarkers TumorHumansComputer SimulationAmino Acid SequenceBiologyCervical carcinomabusiness.industryOligonucleotide Array Sequence AnalysiGene Expression ProfilingCancerComputational Biologymedicine.diseaseChromatin Assembly and DisassemblyGene expression profiling030104 developmental biologyHuman medicinebusinessHeLa CellsOncotarget
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VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy

2017

The possibility of integrating viral vectors to become a persistent part of the host genome makes them a crucial element of clinical gene therapy. However, viral integration has associated risks, such as the unintentional activation of oncogenes that can result in cancer. Therefore, the analysis of integration sites of retroviral vectors is a crucial step in developing safer vectors for therapeutic use. Here we present VISMapper, a vector integration site analysis web server, to analyze next-generation sequencing data for retroviral vector integration sites. VISMapper can be found at: http://vismapper.babelomics.org . Because it uses novel mapping algorithms VISMapper is remarkably faster t…

0301 basic medicineWeb serverVirus IntegrationGenetic enhancementGenetic VectorsContext (language use)Computational biologyBiologyGenoma humàlcsh:Computer applications to medicine. Medical informaticscomputer.software_genreBiochemistryGenome viewerViral vectorViral integrationUser-Computer Interface03 medical and health sciencesGene therapyStructural BiologySAFERViral insertionSequence mappingHumansUltra fastGens Mapatgelcsh:QH301-705.5Molecular BiologyGeneticsInternetBase SequenceApplied MathematicsHigh-Throughput Nucleotide SequencingGenetic Therapy3. Good healthComputer Science Applications030104 developmental biologylcsh:Biology (General)lcsh:R858-859.7Viral integrationDNA microarraycomputerSoftware
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Functional Genomics in Wine Yeast: DNA Arrays and Next Generation Sequencing

2017

Since their very beginning, DNA array and next-generation sequencing technologies have been used with Saccharomyces cerevisiae cells. In the last 7 years, an increasing number of studies have focused on the study of wine strains and winemaking. The uncovering of the genomic features of these strains and expression profiles under the different stressful conditions that they have to deal with have contributed significantly to the knowledge of how this amazing microorganism can convert grape must into a drink that has enormously influenced mankind for 7000 years.This review presents a synopsis of DNA array and next-generation sequencing (NGS) technologies and focus mainly in their use in study…

0301 basic medicineWineGeneticsbiology030106 microbiologySaccharomyces cerevisiaeComputational biologybiology.organism_classificationDNA sequencingTranscriptome03 medical and health sciencesYeast in winemaking030104 developmental biologyDNA microarrayFunctional genomicsWinemaking
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