Search results for "Computer applications to medicine. Medical informatics"

showing 10 items of 166 documents

Modality-specific dysfunctional neural processing of social-abstract and non-social-concrete information in schizophrenia

2021

Highlights • Social/non-social information processing in three modalities was investigated in SZ. • SZ showed reduced activation for social information only in gesture modality. • Reduced activation in SZ was observed for non-social information only in speech. • Neural Neural processing in bimodal condition is not different between patients and controls.

Cognitive NeuroscienceSchizoaffective disorderDysfunctional familylcsh:Computer applications to medicine. Medical informaticsmPFC050105 experimental psychologylcsh:RC346-42903 medical and health sciencesGesture0302 clinical medicineSocialmedicineImage Processing Computer-AssistedHumansSpeech0501 psychology and cognitive sciencesRadiology Nuclear Medicine and imaging10. No inequalityPrefrontal cortexlcsh:Neurology. Diseases of the nervous systemBrain MappingModality (human–computer interaction)medicine.diagnostic_testGestures05 social sciencesRegular ArticleMultimodal processingmedicine.diseaseMagnetic Resonance ImagingNeurologySchizophreniaNeural processingSchizophrenialcsh:R858-859.7Neurology (clinical)PsychologyFunctional magnetic resonance imaging030217 neurology & neurosurgeryCognitive psychologyGestureNeuroImage: Clinical
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JANE: efficient mapping of prokaryotic ESTs and variable length sequence reads on related template genomes

2009

Abstract Background ESTs or variable sequence reads can be available in prokaryotic studies well before a complete genome is known. Use cases include (i) transcriptome studies or (ii) single cell sequencing of bacteria. Without suitable software their further analysis and mapping would have to await finalization of the corresponding genome. Results The tool JANE rapidly maps ESTs or variable sequence reads in prokaryotic sequencing and transcriptome efforts to related template genomes. It provides an easy-to-use graphics interface for information retrieval and a toolkit for EST or nucleotide sequence function prediction. Furthermore, we developed for rapid mapping an enhanced sequence align…

Computational biologyBiologylcsh:Computer applications to medicine. Medical informaticsBiochemistryGenomeUser-Computer InterfaceStructural BiologyDatabases Geneticlcsh:QH301-705.5Molecular BiologySequence (medicine)Expressed Sequence TagsWhole genome sequencingGeneticsInternetExpressed sequence tagGenomeBase SequencePhylumApplied MathematicsNucleic acid sequenceComputational BiologySequence Analysis DNAComputer Science Applicationslcsh:Biology (General)Single cell sequencinglcsh:R858-859.7DNA microarraySoftwareBMC Bioinformatics
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Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.

2007

Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…

Computer scienceAlgorismesPrediction by partial matchingCompression dissimilaritycomputer.software_genreBiochemistryProtein Structure SecondaryPhylogenetic studiesStructural BiologySequence Analysis ProteinDatabases Proteinlcsh:QH301-705.5Biological dataNCDApplied MathematicsGenomicsClassificationCDComputer Science ApplicationsBenchmarking:Informàtica::Informàtica teòrica [Àrees temàtiques de la UPC]Universal compression dissimilarityArea Under CurveMetric (mathematics)lcsh:R858-859.7Data miningAlgorithmsData compressionResearch Article:Informàtica::Aplicacions de la informàtica::Bioinformàtica [Àrees temàtiques de la UPC]Normalization (statistics)lcsh:Computer applications to medicine. Medical informaticsBioinformatics Sequence Alignment AlgorithmsSet (abstract data type)Similarity (network science)Normalized compression sissimilarityData compression (Computer science)AnimalsHumansAmino Acid SequenceMolecular BiologyBiologyDades -- Compressió (Informàtica)USMUniversal similarity metricProteinsUCDProtein Structure TertiaryData setGenòmicaStatistical classificationlcsh:Biology (General)ROC CurvecomputerSequence AlignmentSoftwareBMC bioinformatics
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CORENup: a combination of convolutional and recurrent deep neural networks for nucleosome positioning identification

2020

Abstract Background Nucleosomes wrap the DNA into the nucleus of the Eukaryote cell and regulate its transcription phase. Several studies indicate that nucleosomes are determined by the combined effects of several factors, including DNA sequence organization. Interestingly, the identification of nucleosomes on a genomic scale has been successfully performed by computational methods using DNA sequence as input data. Results In this work, we propose CORENup, a deep learning model for nucleosome identification. CORENup processes a DNA sequence as input using one-hot representation and combines in a parallel fashion a fully convolutional neural network and a recurrent layer. These two parallel …

Computer scienceCelllcsh:Computer applications to medicine. Medical informaticsBiochemistryConvolutional neural networkDNA sequencingchemistry.chemical_compoundStructural BiologyTranscription (biology)medicineHumansNucleosomeA-DNAEpigeneticsMolecular Biologylcsh:QH301-705.5Nucleosome classificationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabiologybusiness.industryApplied MathematicsDeep learningResearchEpigeneticPattern recognitionGenomicsbiology.organism_classificationNucleosomesComputer Science ApplicationsRecurrent neural networkmedicine.anatomical_structurechemistrylcsh:Biology (General)Recurrent neural networkslcsh:R858-859.7Deep learning networksEukaryoteNeural Networks ComputerArtificial intelligenceDNA microarraybusinessDNABMC Bioinformatics
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PVAmpliconFinder: a workflow for the identification of human papillomaviruses from high-throughput amplicon sequencing

2019

Abstract Background The detection of known human papillomaviruses (PVs) from targeted wet-lab approaches has traditionally used PCR-based methods coupled with Sanger sequencing. With the introduction of next-generation sequencing (NGS), these approaches can be revisited to integrate the sequencing power of NGS. Although computational tools have been developed for metagenomic approaches to search for known or novel viruses in NGS data, no appropriate tool is available for the classification and identification of novel viral sequences from data produced by amplicon-based methods. Results We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify kno…

Computer scienceComputational biologylcsh:Computer applications to medicine. Medical informaticsBiochemistryWorkflowUser-Computer Interface03 medical and health sciencessymbols.namesakeStructural BiologyHumansVirus discoverylcsh:QH301-705.5PapillomaviridaeMolecular BiologyThroughput (business)PhylogenyAmplicon sequencing030304 developmental biologySanger sequencing0303 health sciencesBiological data030306 microbiologyMethodology ArticleApplied MathematicsHigh-Throughput Nucleotide SequencingPapillomavirusAmpliconComputer Science ApplicationsIdentification (information)Workflowlcsh:Biology (General)MetagenomicsDNA ViralAmplicon sequencingsymbolslcsh:R858-859.7Primer (molecular biology)DNA microarrayBMC Bioinformatics
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pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

2019

AbstractBackgroundPrincipal component analysis (PCA) is frequently useentirely written ind in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking.ResultsWe developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny fra…

Computer scienceInterface (computing)ShinyBioconductorPrincipal component analysis610 MedizinRNA-SeqGenomicslcsh:Computer applications to medicine. Medical informaticsReproducible researchBioconductorTranscriptomeExploratory data analysisUser-friendly610 Medical sciencesGene expressionHumansRNA-SeqGenelcsh:QH301-705.5Data CurationBase Sequencebusiness.industrySequence Analysis RNARRNAReproducibility of Resultslcsh:Biology (General)Principal component analysisRNAlcsh:R858-859.7Software engineeringbusinessSoftware
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Job strain in public transport drivers: Data to assess the relationship between demand-control model indicators, traffic accidents and sanctions

2018

This Data in Brief (DiB) article examines the association between the Job Demand-Control (JDC) model of stress and traffic safety outcomes (accidents and sanctions) in public transport drivers (n = 780). The data was collected using a structured self-administrable questionnaire composed of measurements of work stress (Job Content Questionnaire), and demographics (professional driving experience, hours and days working/driving per week). The data contains 4 parts: descriptive statistics, bivariate correlations between the study variables, analysis of variance (ANOVA) and Post-Hoc comparisons between drivers classified different quadrants of the JDC model. For further information, it is conve…

Control (management)Applied psychologyWorking conditionsBivariate analysisRendimiento laborallcsh:Computer applications to medicine. Medical informatics03 medical and health sciences0302 clinical medicineJob strainPublic transport driversSanctionsPsychologyTraffic fines0501 psychology and cognitive sciences030212 general & internal medicineDemand-Control Modellcsh:Science (General)Work stressMultidisciplinaryJob strainDescriptive statisticsJDC Job Demand-Control ModelProfessional drivingbusiness.industryTraffic accidents05 social sciences050106 general psychology & cognitive sciencesWork (electrical)Work stressJCQ Job Content QuestionnairePublic transportEstudios de evaluaciónlcsh:R858-859.7businessPsychologyEstrés laborallcsh:Q1-390
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UVPAR: fast detection of functional shifts in duplicate genes.

2006

Abstract Background The imprint of natural selection on gene sequences is often difficult to detect. A plethora of methods have been devised to detect genetic changes due to selective processes. However, many of those methods depend heavily on underlying assumptions regarding the mode of change of DNA sequences and often require sophisticated mathematical treatments that made them computationally slow. The development of fast and effective methods to detect modifications in the selective constraints of genes is therefore of great interest. Results We describe UVPAR, a program designed to quickly test for changes in the functional constraints of duplicate genes. Starting with alignments of t…

DanioComputational biologyBiologylcsh:Computer applications to medicine. Medical informaticsBiochemistryDNA sequencingEvolution MolecularGenes DuplicateSequence Analysis ProteinStructural BiologySelection GeneticHox geneMolecular BiologyGenelcsh:QH301-705.5Selection (genetic algorithm)GeneticsNatural selectionApplied MathematicsProteinsSequence Analysis DNAbiology.organism_classificationComputer Science Applicationslcsh:Biology (General)lcsh:R858-859.7DNA microarraySequence AlignmentSoftwareAlgorithmsGenètica
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Analyzing big datasets of genomic sequences: fast and scalable collection of k-mer statistics

2019

Abstract Background Distributed approaches based on the MapReduce programming paradigm have started to be proposed in the Bioinformatics domain, due to the large amount of data produced by the next-generation sequencing techniques. However, the use of MapReduce and related Big Data technologies and frameworks (e.g., Apache Hadoop and Spark) does not necessarily produce satisfactory results, in terms of both efficiency and effectiveness. We discuss how the development of distributed and Big Data management technologies has affected the analysis of large datasets of biological sequences. Moreover, we show how the choice of different parameter configurations and the careful engineering of the …

Data AnalysisFOS: Computer and information sciencesTime FactorsTime FactorComputer scienceStatistics as TopicBig dataApache Spark; distributed computing; performance evaluation; k-mer countinglcsh:Computer applications to medicine. Medical informaticsBiochemistryDomain (software engineering)Databases03 medical and health sciences0302 clinical medicineStructural BiologyComputer clusterStatisticsSpark (mathematics)Molecular Biologylcsh:QH301-705.5030304 developmental biology0303 health sciencesGenomeSettore INF/01 - InformaticaBase SequenceNucleic AcidApache Sparkbusiness.industryResearchApache Spark; Distributed computing; k-mer counting; Performance evaluation; Algorithms; Base Sequence; Software; Time Factors; Data Analysis; Databases Nucleic Acid; Genome; Statistics as TopicApplied Mathematicsk-mer countingDistributed computingComputer Science ApplicationsAlgorithmData AnalysiComputer Science - Distributed Parallel and Cluster Computinglcsh:Biology (General)030220 oncology & carcinogenesisScalabilityPerformance evaluationlcsh:R858-859.7Algorithm designDistributed Parallel and Cluster Computing (cs.DC)Databases Nucleic AcidbusinessAlgorithmsSoftware
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Technology-Supported Guidance Models Stimulating the Development of Critical Thinking in Clinical Practice: Protocol for a Mixed Methods Systematic R…

2020

BackgroundCritical thinking is an essential skill that nursing students need to develop. Technological tools have opened new avenues for technology-supported guidance models, but the challenges and facilitators of such guidance models, as well as how they stimulate the development of critical thinking, remain unclear.ObjectiveWe developed a protocol for a mixed methods systematic review to investigate the use of technology-supported guidance models that stimulate the development of critical thinking in nursing education clinical practice.MethodsA convergent integrated design following the Joanna Briggs Institute Manual for Evidence Synthesis will be employed. A pair of authors will select t…

Data transformationComputer applications to medicine. Medical informaticsguidance modelsR858-859.703 medical and health sciences0302 clinical medicineProtocolcritical thinking030212 general & internal medicineNurse educationProtocol (science)Medical education030504 nursingClinical study designnursing educationRGeneral Medicineclinical practiceClinical PracticeCritical thinkingData extractiontechnologyMedicine0305 other medical sciencePsychologyEvidence synthesisJMIR Research Protocols
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