Search results for " microarray"

showing 10 items of 196 documents

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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Biotin-Genomic Run-On (Bio-GRO): A High-Resolution Method for the Analysis of Nascent Transcription in Yeast

2016

Transcription is a highly complex biological process, with extensive layers of regulation, some of which remain to be fully unveiled and understood. To be able to discern the particular contributions of the several transcription steps it is crucial to understand RNA polymerase dynamics and regulation throughout the transcription cycle. Here we describe a new nonradioactive run-on based method that maps elongating RNA polymerases along the genome. In contrast with alternative methodologies for the measurement of nascent transcription, the BioGRO method is designed to minimize technical noise that arises from two of the most common sources that affect this type of strategies: contamination wi…

0301 basic medicinebiologySaccharomyces cerevisiaeRNARNA polymerase IIComputational biologybiology.organism_classificationGene expression profiling03 medical and health scienceschemistry.chemical_compound030104 developmental biologychemistryTranscription (biology)RNA polymerasebiology.proteinDNA microarrayPolymerase
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Differential Expression Profiles and Functional Prediction of Circular RNAs in Pediatric Dilated Cardiomyopathy

2020

Circular RNAs (circRNAs) have emerged as essential regulators and biomarkers in various diseases. To assess the different expression levels of circRNAs in pediatric dilated cardiomyopathy (PDCM) and explore their biological and mechanistic significance, we used RNA microarrays to identify differentially expressed circRNAs between three children diagnosed with PDCM and three healthy age-matched volunteers. The biological function of circRNAs was assessed with a circRNA–microRNA (miRNA)–mRNA interaction network constructed from Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Differentially expressed circRNAs were validated by quantitative real-time polymerase chain reaction (qR…

0301 basic medicinecircular RNAs (circRNAs)gene expression profile (GEP)Microarray030204 cardiovascular system & hematologyBiologyBioinformaticsmedicine.disease_causeBiochemistry Genetics and Molecular Biology (miscellaneous)Biochemistrylaw.inventionAutoimmunity03 medical and health sciences0302 clinical medicinepediatric dilated cardiomyopathylawmicroRNAmedicineMolecular BiosciencesKEGGMolecular Biologylcsh:QH301-705.5Polymerase chain reactionOriginal ResearchRNAbiomarkersFold change030104 developmental biologylcsh:Biology (General)DNA microarraymicroarrayFrontiers in Molecular Biosciences
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OSAnalyzer: A Bioinformatics Tool for the Analysis of Gene Polymorphisms Enriched with Clinical Outcomes.

2016

Background: The identification of biomarkers for the estimation of cancer patients’ survival is a crucial problem in modern oncology. Recently, the Affymetrix DMET (Drug Metabolizing Enzymes and Transporters) microarray platform has offered the possibility to determine the ADME (absorption, distribution, metabolism, and excretion) gene variants of a patient and to correlate them with drug-dependent adverse events. Therefore, the analysis of survival distribution of patients starting from their profile obtained using DMET data may reveal important information to clinicians about possible correlations among drug response, survival rate, and gene variants. Methods: In order to provide support …

0301 basic medicinepharmacogenomicoverall survivalBiomedical EngineeringDME genes; genotyping microarrays; overall survival; pharmacogenomics; progression-free survivalBioengineeringBiologyBioinformaticsBiochemistryArticlelcsh:Biochemistrygenotyping microarray03 medical and health sciencesmedicineOverall survivallcsh:QD415-436Progression-free survivalgenotyping microarraysAdverse effectSurvival rateGeneADMEpharmacogenomicsADME geneCancermedicine.diseaseADME genesgenotyping microarrays; ADME genes; pharmacogenomics; overall survival; progression-free survival030104 developmental biologyPharmacogenomicsprogression-free survivalBiotechnologyMicroarrays (Basel, Switzerland)
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Expression profile of genes involved in hydrogen sulphide liberation by Saccharomyces cerevisiae grown under different nitrogen concentrations

2009

AbstractThe present work aims to elucidate molecular mechanisms underlying hydrogen sulphide production in S. cerevisiae associated to nitrogen deficiency. To assess, at a genome-wide level, how the yeast strain adapted to the progressive nitrogen depletion and to nitrogen re-feeding, gene expression profiles were evaluated during fermentation at different nitrogen concentrations, using the DNA array technology. The results showed that most MET genes displayed higher expression values at the beginning of both control and N-limiting fermentation, just before the time at which the release of sulphide was observed. MET genes were downregulated when yeast stopped growing which could associate M…

0303 health sciencesbiologyChemistryNitrogen deficiencySaccharomyces cerevisiaebiology.organism_classificationYeast03 medical and health scienceschemistry.chemical_compound0302 clinical medicineBiosynthesisBiochemistry030220 oncology & carcinogenesisGene expressionGeneral Materials ScienceFermentationDNA microarrayGene030304 developmental biologyNature Precedings
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A hybrid short read mapping accelerator

2013

Background The rapid growth of short read datasets poses a new challenge to the short read mapping problem in terms of sensitivity and execution speed. Existing methods often use a restrictive error model for computing the alignments to improve speed, whereas more flexible error models are generally too slow for large-scale applications. A number of short read mapping software tools have been proposed. However, designs based on hardware are relatively rare. Field programmable gate arrays (FPGAs) have been successfully used in a number of specific application areas, such as the DSP and communications domains due to their outstanding parallel data processing capabilities, making them a compet…

:Engineering::Computer science and engineering [DRNTU]GenomeComputer sciencebusiness.industryApplied MathematicsMethodology ArticleChromosome MappingSequence Analysis DNABiochemistryComputer Science ApplicationsSoftwareComputer engineeringStructural BiologySensitivity (control systems)DNA microarraybusinessField-programmable gate arrayAlgorithmMolecular BiologySequence AlignmentDigital signal processingAlgorithmsSoftwareReference genomeBMC Bioinformatics
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An improvement of ComiR algorithm for microRNA target prediction by exploiting coding region sequences of mRNAs

2020

AbstractMicroRNA are small non-coding RNAs that post-transcriptionally regulate the expression levels of messenger RNAs. MicroRNA regulation activity depends on the recognition of binding sites located on mRNA molecules. ComiR is a web tool realized to predict the targets of a set of microRNAs, starting from their expression profile. ComiR was trained with the information regarding binding sites in the 3’utr region, by using a reliable dataset containing the targets of endogenously expressed microRNA in D. melanogaster S2 cells. This dataset was obtained by comparing the results from two different experimental approaches, i.e., inhibition, and immunoprecipitation of the AGO1 protein--a comp…

AGO1ImmunoprecipitationComputer sciencelcsh:Computer applications to medicine. Medical informaticsBiochemistryOpen Reading Frames03 medical and health sciences0302 clinical medicineStructural BiologymicroRNAMelanogasterAnimalsHumansCoding regionGene silencing3'UTRRNA MessengerBinding sitelcsh:QH301-705.5Molecular Biology030304 developmental biology0303 health sciencesMessenger RNAbiologyThree prime untranslated regionResearchApplied MathematicsmicroRNA target predictionbiology.organism_classificationComputer Science Applications3’UTRMicroRNAsDrosophila melanogasterlcsh:Biology (General)Coding regionlcsh:R858-859.7DNA microarrayDrosophila melanogasterAlgorithmAlgorithms030217 neurology & neurosurgeryBMC Bioinformatics
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Genome and phenotype microarray analyses of rhodococcus sp. BCP1 and rhodococcus opacus R7: Genetic determinants and metabolic abilities with environ…

2015

In this paper comparative genome and phenotype microarray analyses of Rhodococcus sp. BCP1 and Rhodococcus opacus R7 were performed. Rhodococcus sp. BCP1 was selected for its ability to grow on short-chain n-alkanes and R. opacus R7 was isolated for its ability to grow on naphthalene and on o-xylene. Results of genome comparison, includ- ing BCP1, R7, along with other Rhodococcus reference strains, showed that at least 30% of the genome of each strain presented unique sequences and only 50% of the predicted proteome was shared. To associate genomic features with metabolic capabilities of BCP1 and R7 strains, hundreds of different growth conditions were tested through Phenotype Microarray, b…

AROMATIC-COMPOUNDS; GENUS RHODOCOCCUS; HIGH-THROUGHPUT; PATHWAY; DEGRADATION; BIODEGRADATION; EQUI; PERFORMANCE; CATABOLISMGenomics RhodococcusGene predictionBacterial Proteinlcsh:MedicineBiologyGenomeXenobioticsRhodococcus opacusBacterial ProteinsRhodococcuslcsh:ScienceGenePhylogenyGeneticsComparative genomicsMultidisciplinarylcsh:RMetabolic Networks and PathwayPhenotype microarrayHigh-Throughput Nucleotide SequencingRhodococcus sp. BCP1 Rhodococcus opacus R7Genome analysisGene Expression Regulation BacterialGenomicsSequence Analysis DNAbiology.organism_classificationBIO/19 - MICROBIOLOGIA GENERALEBiodegradation EnvironmentalPhenotypeProteomeGenomiclcsh:QPhenotype MicroarrayRhodococcusMetabolic Networks and PathwaysRhodococcuhydrocarbon degradationResearch Article
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