Search results for "Application"

showing 10 items of 5559 documents

Revisitation of Nonorthogonal Spin Adaptation in Coupled Cluster Theory.

2015

The benefits of what is alternatively called a nonorthogonally spin-adapted, spin-free, or orbital representation of the coupled cluster equations is discussed relative to orthogonally spin-adapted, spin-orbital, and spin-integrated theories. In particular, specific linear combinations of the orbital cluster amplitudes, denoted spin-summed amplitudes, are shown to reduce the number of contractions that must be explicitly performed and to simplify the expressions and their derivation. The computational efficiency of the spin-summed approach is discussed and compared to orthogonally spin-adapted and spin-integrated approaches. The spin-summed approach is shown to have significant computationa…

Computer scienceAdaptation (eye)computer.software_genreComputer Science ApplicationsAmplitudeCoupled clusterCluster (physics)Condensed Matter::Strongly Correlated ElectronsData miningStatistical physicsPhysical and Theoretical ChemistryRepresentation (mathematics)Linear combinationcomputerSpin-½Journal of chemical theory and computation
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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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Dynamic-shared Pharmacophore Approach as Tool to Design New Allosteric PRC2 Inhibitors, Targeting EED Binding Pocket.

2020

Abstract: The Polycomb Repressive complex 2 (PRC2) maintains a repressive chromatin state and silences many genes, acting as methylase on histone tails. This enzyme was found overexpressed in many types of cancer. In this work, we have set up a Computer-Aided Drug Design approach based on the allosteric modulation of PRC2. In order to minimize the possible bias derived from using a single set of coordinates within the protein-ligand complex, a dynamic workflow was developed. In details, molecular dynamic was used as tool to identify the most significant ligand-protein interactions from several crystallized protein structures. The identified features were used for the creation of dynamic pha…

Computer scienceAllosteric regulationBinding pocketmacromolecular substancesComputational biologyMolecular Dynamics SimulationLigands01 natural sciences03 medical and health sciencesProtein structureStructural BiologyDrug DiscoveryHumans030304 developmental biologyEED0303 health sciencesVirtual screeningBinding SitesbiologyOrganic ChemistryMolecular DynamicPolycomb Repressive Complex 2Dynamic pharmacophorePRC20104 chemical sciencesComputer Science ApplicationsChromatinMolecular Docking Simulation010404 medicinal & biomolecular chemistryROC CurveDocking (molecular)Drug Designbiology.proteinMolecular MedicinePharmacophorePRC2Allosteric SiteProtein BindingMolecular informaticsReferences
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A Non-Stationary Channel Model for the Development of Non-Wearable Radio Fall Detection Systems

2018

The emerging non-wearable fall detection systems rely on processing radio waves reflected off the body of the home user who has no active interaction with the system, increasing the user privacy and acceptability. This paper proposes a nonstationary channel model that is important for the development of such systems. A three-dimensional stochastic trajectory model is designed to capture targeted mobility patterns of the home user. The model is featured with a forward fall mechanism, which is actuated at a random point along the path. A transmitter emits radio waves throughout an indoor propagation environment, while a receiver collects fingerprints of the scattering objects on the emitted w…

Computer scienceApplied MathematicsReal-time computingTransmitterSpectral density020206 networking & telecommunications02 engineering and technologyComputer Science Applicationssymbols.namesake0202 electrical engineering electronic engineering information engineeringsymbols020201 artificial intelligence & image processingElectrical and Electronic EngineeringDoppler effectCommunication channelRadio wave
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Bayesian inference in Markovian queues

1994

This paper is concerned with the Bayesian analysis of general queues with Poisson input and exponential service times. Joint posterior distribution of the arrival rate and the individual service rate is obtained from a sample consisting inn observations of the interarrival process andm complete service times. Posterior distribution of traffic intensity inM/M/c is also obtained and the statistical analysis of the ergodic condition from a decision point of view is discussed.

Computer scienceBayesian probabilityErgodicityPosterior probabilityManagement Science and Operations ResearchBayesian inferencePoisson distributionComputer Science ApplicationsExponential functionTraffic intensitysymbols.namesakeComputational Theory and MathematicsStatisticssymbolsApplied mathematicsErgodic theoryQueueing Systems
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Portable low-cost open-source wireless spectrophotometer for fast and reliable measurements

2020

This article is based upon COST Action CA16215 and supported by the ERDF , European-Union Project No.1.1.1.2/16/I/001.

Computer scienceBiomedical EngineeringMobile application01 natural sciencesSpectrometerIndustrial and Manufacturing EngineeringAbsorptionSet (abstract data type)03 medical and health sciencesSoftwareArduino:NATURAL SCIENCES:Physics [Research Subject Categories]ArduinoWirelesslcsh:Science (General)InstrumentationSpectroscopy030304 developmental biologyCivil and Structural EngineeringDetection limit0303 health sciencesMeasure (data warehouse)Spectrometerbusiness.industryDynamic rangeMechanical Engineering010401 analytical chemistry0104 chemical sciencesbusinessComputer hardwarelcsh:Q1-390HardwareX
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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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Computation of Psycho-Acoustic Annoyance Using Deep Neural Networks

2019

Psycho-acoustic parameters have been extensively used to evaluate the discomfort or pleasure produced by the sounds in our environment. In this context, wireless acoustic sensor networks (WASNs) can be an interesting solution for monitoring subjective annoyance in certain soundscapes, since they can be used to register the evolution of such parameters in time and space. Unfortunately, the calculation of the psycho-acoustic parameters involved in common annoyance models implies a significant computational cost, and makes difficult the acquisition and transmission of these parameters at the nodes. As a result, monitoring psycho-acoustic annoyance becomes an expensive and inefficient task. Thi…

Computer scienceComputationsubjective annoyanceContext (language use)Annoyance02 engineering and technologycomputer.software_genre01 natural sciencesConvolutional neural networklcsh:TechnologyReduction (complexity)lcsh:Chemistryconvolutional neural networks0202 electrical engineering electronic engineering information engineeringWirelessGeneral Materials Sciencewireless acoustic sensor networksInstrumentationlcsh:QH301-705.5Fluid Flow and Transfer Processesbusiness.industrylcsh:TProcess Chemistry and Technology010401 analytical chemistryGeneral EngineeringRegression analysislcsh:QC1-9990104 chemical sciencesComputer Science Applicationspsycho-acoustic parametersTransmission (telecommunications)lcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040020201 artificial intelligence & image processingData miningbusinesslcsh:Engineering (General). Civil engineering (General)Zwicker modelcomputerlcsh:PhysicsApplied Sciences
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A multi-domain approach for smoothed particle hydrodynamics simulations of highly complex flows

2018

Abstract An efficient and accurate method is proposed to solve the incompressible flow momentum and continuity equations in computational domains partitioned into subdomains in the framework of the smoothed particle hydrodynamics method. The procedure does not require any overlap of the subdomains, which would result in the increase of the computational effort. Perfectly matching solutions are obtained at the surfaces separating neighboring blocks. The block interfaces can be both planar and curved surfaces allowing to easily decompose even geometrically complex domains. The smoothing length of the kernel function is maintained constant in each subdomain, while changing between blocks where…

Computer scienceComputational MechanicsGeneral Physics and AstronomyBoundary condition010103 numerical & computational mathematics01 natural sciencesSettore ICAR/01 - IdraulicaMomentumSmoothed-particle hydrodynamicsPhysics and Astronomy (all)Smoothed particle hydrodynamicIncompressible flowComputational mechanicsMechanics of MaterialDomain decomposition0101 mathematicsMirror particleComputational MechanicConservation of massISPHBlock (data storage)Mechanical EngineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionDomain decomposition methodsComputer Science Applications010101 applied mathematicsMechanics of MaterialsMulti-blockAlgorithmSmoothingComputer Methods in Applied Mechanics and Engineering
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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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