Search results for " microarray"

showing 10 items of 196 documents

Speeding up the Consensus Clustering methodology for microarray data analysis

2010

Abstract Background The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose…

Settore INF/01 - Informaticalcsh:QH426-470Computer scienceResearchApplied MathematicsStability (learning theory)InferenceApproximation algorithmcomputer.software_genreNon-negative matrix factorizationIdentification (information)lcsh:GeneticsComputingMethodologies_PATTERNRECOGNITIONComputational Theory and Mathematicslcsh:Biology (General)Structural BiologyConsensus clusteringBenchmark (computing)Data mininginternal validation measures data mining microarray data NMFCluster analysiscomputerMolecular Biologylcsh:QH301-705.5Algorithms for Molecular Biology
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proTRAC - a software for probabilistic piRNA cluster detection, visualization and analysis

2012

Abstract Background Throughout the metazoan lineage, typically gonadal expressed Piwi proteins and their guiding piRNAs (~26-32nt in length) form a protective mechanism of RNA interference directed against the propagation of transposable elements (TEs). Most piRNAs are generated from genomic piRNA clusters. Annotation of experimentally obtained piRNAs from small RNA/cDNA-libraries and detection of genomic piRNA clusters are crucial for a thorough understanding of the still enigmatic piRNA pathway, especially in an evolutionary context. Currently, detection of piRNA clusters relies on bioinformatics rather than detection and sequencing of primary piRNA cluster transcripts and the stringency …

Small RNAendocrine systemLineage (evolution)Piwi-interacting RNAGenomicsContext (language use)Computational biologyBiologylcsh:Computer applications to medicine. Medical informaticsBiochemistryMiceStructural BiologyCluster (physics)AnimalsHumansGenomic libraryRNA Small InterferingMolecular Biologylcsh:QH301-705.5Gene LibraryGeneticsurogenital systemApplied MathematicsGenomicsComputer Science ApplicationsRatslcsh:Biology (General)DNA Transposable Elementslcsh:R858-859.7RNA InterferenceDNA microarraySoftwareBMC Bioinformatics
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Molecular mechanisms of sorafenib action in liver cancer cells.

2012

Sorafenib, a multikinase inhibitor, recently received FDA approval for the treatment of advanced hepatocellular carcinoma (HCC). However, as the clinical application of sorafenib evolves, there is increasing interest in defining the mechanisms underlying its anti-tumor activity. Considering that this specific inhibitor could target unexpected molecules depending on the biologic context, a precise understanding of its mechanism of action could be critical to maximize its treatment efficacy, while minimizing adverse effects. Two human HCC cell lines (HepG2 and Huh7), carrying different biological and genetic characteristics, were used in this study to examine the intracellular events leading …

SorafenibDNA ReplicationNiacinamideCarcinoma HepatocellularDNA RepairTranscription GeneticAngiogenesisCell SurvivalPyridinesApoptosisPharmacologyBiologysorafenib HCC mini-chromosome maintenance genes Dickkopf1 Harakiri Acheron/LARP6 YAP1 cell cycle microarray global gene expression analysisCell Line TumormedicineCell AdhesionHumansneoplasmsMolecular BiologyProtein Kinase InhibitorsCell ProliferationYAP1Neovascularization PathologicCell growthGene Expression ProfilingPhenylurea CompoundsBenzenesulfonatesCell CycleLiver NeoplasmsBiological TransportCell BiologyCell cycleSorafenibmedicine.diseasedigestive system diseasesMechanism of actionHepatocellular carcinomaProtein Biosynthesismedicine.symptomMitogen-Activated Protein KinasesLiver cancerDevelopmental Biologymedicine.drugSignal Transduction
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Titelbild: Tumor-Associated MUC1 Tandem-Repeat Glycopeptide Microarrays to Evaluate Serum- and Monoclonal-Antibody Specificity (Angew. Chem. 44/2009)

2009

Tandem repeatBiochemistryChemistrymedicine.drug_classmedicineGeneral MedicineDNA microarrayMonoclonal antibodyMolecular biologyGlycopeptideMUC1Angewandte Chemie
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Splenic Marginal Zone Lymphoma Shows a Distinct Pattern of DNA Copy Number Aberrations That Correlates with Tumor Characteristics and Predicts Diseas…

2006

Abstract Splenic marginal zone lymphoma (SMZL) is an indolent B cell malignancy whose diagnosis is based on lymphocyte morphology, immunophenotype and marrow and/or splenic histology. Unlike other lymphomas, there is not a common chromosomal translocation specific for SMZL, and genetic prognostic factors are poorly defined. To investigate the pattern of genomic aberrations in SMZL, we applied comparative genomic hybridization to BAC microarrays (array CGH) to a well characterized series of 75 SMZL specimens. We applied two different 1 Mb-resolution BAC arrays: UCSF HumArray 3.2 and a novel array CGH platform developed at Univ. of Salamanca. These arrays allowed us to detect DNA copy number …

Tissue microarrayImmunologyFollicular lymphomaCell BiologyHematologyBiologymedicine.diseaseBiochemistryMolecular biologyLymphomaImmunophenotypingComplex KaryotypemedicineMantle cell lymphomaSplenic marginal zone lymphomaComparative genomic hybridizationBlood
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Genomics of mRNA turnover

2007

Most studies on eukaryotic gene regulation have focused on mature mRNA levels. Nevertheless, the steady-state mRNA level is the result of two opposing biological processes: transcription and degradation, both of which can be important points to regulate gene expression. It is now possible to determine the transcription and degradation rates (TR and DR), as well as the mRNA amount, for each gene using DNA chip technologies. In this way, each individual contribution to gene expression can be analysed. This review will deal with the techniques used for the genomic evaluation of TR and DR developed for the yeast Saccharomyces cerevisiae. They will be described in detail and their potential draw…

Transcription GeneticMature messenger RNARNA StabilitySaccharomyces cerevisiaeADNGenomicsComputational biologySaccharomyces cerevisiaeBiologyBiochemistryTranscripció genèticaTranscription (biology)Gene Expression Regulation FungalGene expressionGeneticsAnimalsRNA MessengerMolecular BiologyGeneGeneticsMessenger RNAGenomicsbiology.organism_classificationGenòmicaRNADNA microarray
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DNA chips for yeast biotechnology. The case of wine yeasts.

2002

The yeast Saccharomyces cerevisiae is one of the most popular model organisms. It was the first eukaryote whose genome was sequenced. Since then many functional analysis projects have tried to find the function of many genes and to understand its metabolism in a holistic way. Apart from basic science this microorganism is of great interest in several biotechnology processes, such as winemaking. Only global studies of the cell as a whole can help us to understand many of the technical problems facing winemaking. DNA chip technology is one of the most promising tools for the analysis of cell physiology. Yeast has been the model organism for the development of this technique. Many of the studi…

Transcription Geneticved/biology.organism_classification_rank.speciesSaccharomyces cerevisiaeGene ExpressionBioengineeringWineSaccharomyces cerevisiaeBiologyApplied Microbiology and BiotechnologyGenomeModel organismWinemakingOligonucleotide Array Sequence AnalysisWineEthanolved/biologybusiness.industryfood and beveragesGeneral MedicineSequence Analysis DNAbiology.organism_classificationBiological EvolutionYeastBiotechnologyYeast in winemakingGene Expression RegulationFermentationCarbohydrate MetabolismDNA microarrayGenome FungalbusinessBiotechnologyJournal of biotechnology
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A genomic view of mRNA turnover in yeast

2011

The steady-state mRNA level is the result of two opposing processes: transcription and degradation; both of which can provide important points to regulate gene expression. In the model organism yeast Saccharomyces cerevisiae, it is now possible to determine, at the genomic level, the transcription and degradation rates, as well as the mRNA amount, using DNA chip or parallel sequencing technologies. In this way, the contribution of both rates to individual and global gene expressions can be analysed. Here we review the techniques used for the genomic evaluation of the transcription and degradation rates developed for this yeast, and we discuss the integration of the data obtained to fully an…

Transcription Geneticved/biology.organism_classification_rank.speciesSaccharomyces cerevisiaeSaccharomyces cerevisiaeComputational biologyGeneral Biochemistry Genetics and Molecular BiologyTranscripció genèticaStress PhysiologicalTranscription (biology)YeastsGene expressionRNA MessengerModel organismGeneGeneticsMassive parallel sequencingGeneral Immunology and Microbiologybiologyved/biologyRNA FungalGenomicsGeneral Medicinebiology.organism_classificationYeastGenòmicaRNAGenome FungalDNA microarrayTranscriptomeGeneral Agricultural and Biological SciencesComptes Rendus Biologies
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Infrequent promoter methylation of the MGMT gene in liver metastases from uveal melanoma.

2008

Uveal melanoma is associated with a high mortality rate once metastases occur, with over >90% of metastatic patients dying within less than 1 year from metastases to the liver. The intraarterial hepatic (iah) administration of the alkylating agent fotemustine holds some promise with response rates of 36% and median survival of 15 months. Here, we investigated whether the DNA-repair-protein MGMT may be involved in the variability of response to fotemustine and temozolomide in uveal melanoma. Epigenetic inactivation of MGMT has been demonstrated to be a predictive marker for benefit from alkylating agent therapy in glioblastoma. We found a methylated MGMT promoter in 6% of liver metastases fr…

Uveal NeoplasmsCancer ResearchPathologymedicine.medical_specialtyProtein Array AnalysisAntineoplastic AgentsBiologyMetastasischemistry.chemical_compoundPredictive Value of TestsmedicineBiomarkers TumorHumansPromoter Regions GeneticneoplasmsDNA Modification MethylasesMelanomaTemozolomidePredictive markerTissue microarrayMelanomaTumor Suppressor ProteinsLiver NeoplasmsCancerDNA Methylationmedicine.diseaseImmunohistochemistrydigestive system diseasesNitrogen mustardDNA Repair EnzymesOncologychemistryCancer researchFotemustinemedicine.drugInternational journal of cancer
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Convolutional architectures for virtual screening

2020

Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …

Virtual screeningComputer sciencelcsh:Computer applications to medicine. Medical informaticsMachine learningcomputer.software_genre01 natural sciencesBiochemistryDrug design03 medical and health sciencesUser-Computer InterfaceStructural Biology0103 physical sciencesRepresentation (mathematics)lcsh:QH301-705.5Molecular BiologyBioactivity predictionSelection (genetic algorithm)030304 developmental biologySettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni0303 health sciencesVirtual screening010304 chemical physicsbusiness.industryApplied MathematicsResearchProcess (computing)Deep learningComputer Science Applicationslcsh:Biology (General)Molecular fingerprintslcsh:R858-859.7Artificial intelligenceDNA microarraybusinesscomputerAlgorithmsBMC Bioinformatics
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