Search results for "Computer Science Applications"

showing 10 items of 3993 documents

Cortical Reorganization after Rehabilitation in a Patient with Conduction Aphasia Using High-Density EEG

2020

Conduction aphasia is a language disorder occurred after a left-brain injury. It is characterized by fluent speech production, reading, writing and normal comprehension, while speech repetition is impaired. The aim of this study is to investigate the cortical responses, induced by language activities, in a sub-acute stroke patient affected by conduction aphasia before and after an intensive speech therapy training. The patient was examined by using High-Density Electroencephalogram (HD-EEG) examination, while was performing language tasks. the patient was evaluated at baseline and after two months after rehabilitative treatment. Our results showed that an intensive rehabilitative process, i…

0301 basic medicineSpeech productionmedicine.medical_specialtymedicine.medical_treatmentlcsh:Technologyrehabilitationlcsh:Chemistry03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationConduction aphasiaNeuroplasticitymedicineGeneral Materials ScienceLanguage disorderInstrumentationStrokelcsh:QH301-705.5Fluid Flow and Transfer ProcessesHigh-Density EEGRehabilitationbusiness.industrylcsh:TProcess Chemistry and TechnologyGeneral Engineeringmedicine.diseaselcsh:QC1-999Computer Science ApplicationsComprehension030104 developmental biologylcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Speech repetitionbusinessconduction aphasialcsh:Engineering (General). Civil engineering (General)brain plasticity030217 neurology & neurosurgerylcsh:PhysicsApplied Sciences
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Assessing statistical significance in multivariable genome wide association analysis

2016

Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whe…

0301 basic medicineStatistics and Probability1303 BiochemistryGenotypeOperations researchLibrary sciencePolymorphism Single NucleotideBiochemistryGerman03 medical and health sciences10007 Department of EconomicsPolitical scienceGenome-Wide Association Analysis1312 Molecular Biology1706 Computer Science ApplicationsCluster AnalysisHumansComputer Simulation2613 Statistics and ProbabilityMolecular BiologyEuropean researchGenetics and Population AnalysisComputational BiologyReproducibility of ResultsOriginal Paperslanguage.human_languageComputer Science Applications330 EconomicsComputational MathematicsPhenotype030104 developmental biologyComputational Theory and MathematicsLinear Modelslanguage2605 Computational MathematicsGenome-Wide Association Study1703 Computational Theory and Mathematics
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SpaceScanner: COPASI wrapper for automated management of global stochastic optimization experiments

2017

Abstract Motivation Due to their universal applicability, global stochastic optimization methods are popular for designing improvements of biochemical networks. The drawbacks of global stochastic optimization methods are: (i) no guarantee of finding global optima, (ii) no clear optimization run termination criteria and (iii) no criteria to detect stagnation of an optimization run. The impact of these drawbacks can be partly compensated by manual work that becomes inefficient when the solution space is large due to combinatorial explosion of adjustable parameters or for other reasons. Results SpaceScanner uses parallel optimization runs for automatic termination of optimization tasks in case…

0301 basic medicineStatistics and ProbabilityComputer science0206 medical engineeringComputational Biology02 engineering and technologycomputer.software_genreModels BiologicalBiochemistryComputer Science ApplicationsSet (abstract data type)03 medical and health sciencesComputational Mathematics030104 developmental biologyComputational Theory and MathematicsStochastic optimizationData miningMolecular BiologycomputerSoftware020602 bioinformaticsCombinatorial explosionBioinformatics
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Partitioned learning of deep Boltzmann machines for SNP data.

2016

Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…

0301 basic medicineStatistics and ProbabilityComputer scienceMachine learningcomputer.software_genre01 natural sciencesBiochemistryPolymorphism Single NucleotideMachine Learning010104 statistics & probability03 medical and health sciencessymbols.namesakeJoint probability distributionHumans0101 mathematicsMolecular BiologyStatistical hypothesis testingArtificial neural networkbusiness.industryGene Expression Regulation LeukemicDeep learningUnivariateComputational BiologyManifoldComputer Science ApplicationsData setComputational Mathematics030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONComputational Theory and MathematicsLeukemia MyeloidBoltzmann constantsymbolsData miningArtificial intelligencebusinesscomputerSoftwareCurse of dimensionalityBioinformatics (Oxford, England)
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FLYCOP: metabolic modeling-based analysis and engineering microbial communities

2018

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0301 basic medicineStatistics and ProbabilityComputer scienceMetaboliteAuxotrophy030106 microbiologyMicrobial ConsortiaEccb 2018: European Conference on Computational Biology ProceedingsEvolutionary engineeringmedicine.disease_causeBiochemistry03 medical and health scienceschemistry.chemical_compoundmedicineEscherichia coliMetabolic modelingMolecular BiologyEscherichia coli2. Zero hungerbiologyMicrobiotaSystemsBiological evolutionSynechococcusbiology.organism_classificationComputer Science ApplicationsComputational MathematicsMulticellular organism030104 developmental biologyComputational Theory and MathematicschemistryMetabolic EngineeringBiochemical engineeringSoftwareBioinformatics
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MetaCache: context-aware classification of metagenomic reads using minhashing.

2017

Abstract Motivation Metagenomic shotgun 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 corresponding software tools suffer from either long runtimes, large memory requirements or low accuracy. Results We introduce MetaCache—a novel software for read classification using the big data technique minhashing. Our…

0301 basic medicineStatistics and ProbabilityComputer scienceSequence analysisContext (language use)BiochemistryGenome03 medical and health scienceschemistry.chemical_compound0302 clinical medicineRefSeqHumansMolecular BiologyInformation retrievalShotgun sequencingHigh-Throughput Nucleotide SequencingSequence Analysis DNAComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicschemistryMetagenomicsMetagenomics030217 neurology & neurosurgeryDNAAlgorithmsSoftwareReference genomeBioinformatics (Oxford, England)
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Reactome diagram viewer: data structures and strategies to boost performance

2017

Abstract Motivation Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, Reactome uses a custom pathway diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability and performance based on extensive usability testing sessions and technology developments, aiming to optimize the viewer towards the needs of the community. Results The pathway diagram viewer version 3 achieves consistently better performance, loading and rendering of 97% of the diagrams in Reactome in less than 1 s. Combining the multi-layer html5 canvas strategy with a space partit…

0301 basic medicineStatistics and ProbabilityDatabases FactualComputer scienceKnowledge BasesDatabases and OntologiesBiochemistryWorld Wide Web03 medical and health sciences0302 clinical medicineHumansMolecular BiologyInternetComputational BiologyData structureOriginal PapersComputer Science ApplicationsVisualizationComputational Mathematics030104 developmental biologyComputational Theory and Mathematics030220 oncology & carcinogenesisScalabilityAlgorithmsMetabolic Networks and PathwaysSoftwareBioinformatics
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Small RNA-seq analysis of circulating miRNAs to identify phenotypic variability in Friedreich's ataxia patients.

2018

AbstractFriedreich’s ataxia (FRDA; OMIM 229300), an autosomal recessive neurodegenerative mitochondrial disease, is the most prevalent hereditary ataxia. In addition, FRDA patients have shown additional non-neurological features such as scoliosis, diabetes, and cardiac complications. Hypertrophic cardiomyopathy, which is found in two thirds of patients at the time of diagnosis, is the primary cause of death in these patients. Here, we used small RNA-seq of microRNAs (miRNAs) purified from plasma samples of FRDA patients and controls. Furthermore, we present the rationale, experimental methodology, and analytical procedures for dataset analysis. This dataset will facilitate the identificatio…

0301 basic medicineStatistics and ProbabilityEpigenomicsSmall RNAData DescriptorAtaxiaMitochondrial diseaseLibrary and Information SciencesBioinformaticsEducation03 medical and health sciences0302 clinical medicinemicroRNAMedicineHumansCirculating MicroRNAPathologicalCause of deathbusiness.industrySequence Analysis RNAHypertrophic cardiomyopathyNeuromuscular diseasemedicine.diseasePhenotypeComputer Science Applications030104 developmental biologyFriedreich AtaxiaNext-generation sequencingmedicine.symptomStatistics Probability and Uncertaintybusiness030217 neurology & neurosurgeryInformation SystemsScientific data
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ParDRe: faster parallel duplicated reads removal tool for sequencing studies

2016

This is a pre-copyedited, author-produced version of an article accepted for publication in Bioinformatics following peer review. The version of record [insert complete citation information here] is available online at: https://doi.org/10.1093/bioinformatics/btw038 [Abstract] Summary: Current next generation sequencing technologies often generate duplicated or near-duplicated reads that (depending on the application scenario) do not provide any interesting biological information but can increase memory requirements and computational time of downstream analysis. In this work we present ParDRe , a de novo parallel tool to remove duplicated and near-duplicated reads through the clustering of S…

0301 basic medicineStatistics and ProbabilityFASTQ formatDNA stringsSource codeDownstream (software development)Computer sciencemedia_common.quotation_subjectParallel computingcomputer.software_genreBiochemistryDNA sequencing03 medical and health scienceschemistry.chemical_compound0302 clinical medicineHybrid MPI/multithreadingCluster AnalysisParDReMolecular BiologyGenemedia_commonHigh-Throughput Nucleotide SequencingSequence Analysis DNAParallel toolComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicschemistryData miningcomputerAlgorithms030217 neurology & neurosurgeryDNABioinformatics
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Identification and visualization of differential isoform expression in RNA-seq time series

2018

Abstract Motivation As sequencing technologies improve their capacity to detect distinct transcripts of the same gene and to address complex experimental designs such as longitudinal studies, there is a need to develop statistical methods for the analysis of isoform expression changes in time series data. Results Iso-maSigPro is a new functionality of the R package maSigPro for transcriptomics time series data analysis. Iso-maSigPro identifies genes with a differential isoform usage across time. The package also includes new clustering and visualization functions that allow grouping of genes with similar expression patterns at the isoform level, as well as those genes with a shift in major …

0301 basic medicineStatistics and ProbabilityGene isoformIdentificationComputer scienceSequence analysisGene ExpressionRNA-SeqComputational biologyBiochemistryBioconductorTranscriptomeMice03 medical and health sciences0302 clinical medicineEstadística e Investigación OperativaRNA IsoformsAnimalsMolecular BiologyGeneVisualizationRegulation of gene expressionB-LymphocytesSequence Analysis RNAGene Expression ProfilingCell DifferentiationApplications NotesComputer Science ApplicationsVisualizationComputational Mathematics030104 developmental biologyGene Expression RegulationComputational Theory and MathematicsRNA-seq time seriesSoftware030217 neurology & neurosurgeryIsoform expression
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