Search results for "informatica"

showing 10 items of 1003 documents

Alignment-free Genomic Analysis via a Big Data Spark Platform

2021

Abstract Motivation Alignment-free distance and similarity functions (AF functions, for short) are a well-established alternative to pairwise and multiple sequence alignments for many genomic, metagenomic and epigenomic tasks. Due to data-intensive applications, the computation of AF functions is a Big Data problem, with the recent literature indicating that the development of fast and scalable algorithms computing AF functions is a high-priority task. Somewhat surprisingly, despite the increasing popularity of Big Data technologies in computational biology, the development of a Big Data platform for those tasks has not been pursued, possibly due to its complexity. Results We fill this impo…

FOS: Computer and information sciencesStatistics and Probabilitysequence analysisComputer science0206 medical engineeringBig data02 engineering and technologyMachine learningcomputer.software_genreBiochemistry03 medical and health sciencesSpark (mathematics)MapReduceMolecular Biology030304 developmental biology0303 health sciencesSettore INF/01 - Informaticabusiness.industryBioinformatics High Performance Computing Compressed Data StructuresMapReduce; hadoop; sequence analysisComputer Science ApplicationsComputational MathematicsTask (computing)Computer Science - Distributed Parallel and Cluster ComputingComputational Theory and MathematicsDistributed Parallel and Cluster Computing (cs.DC)Artificial intelligencehadoopbusinesscomputer020602 bioinformaticsBioinformatics
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Quantum GestART: Identifying and Applying Correlations between Mathematics, Art, and Perceptual Organization

2020

Mathematics can help analyze the arts and inspire new artwork. Mathematics can also help make transformations from one artistic medium to another, considering exceptions and choices, as well as artists' individual and unique contributions. We propose a method based on diagrammatic thinking and quantum formalism. We exploit decompositions of complex forms into a set of simple shapes, discretization of complex images, and Dirac notation, imagining a world of "prototypes" that can be connected to obtain a fine or coarse-graining approximation of a given visual image. Visual prototypes are exchanged with auditory ones, and the information (position, size) characterizing visual prototypes is con…

FOS: Computer and information sciencesdiagrams; Dirac notation; Gestalt; Gestural similarity; sonificationmedia_common.quotation_subjectHistory and Overview (math.HO)ComputerApplications_COMPUTERSINOTHERSYSTEMSThe artsGestaltBra–ket notationPerceptionGestural similarityFOS: MathematicssonificationQuantummedia_commonCognitive scienceSettore INF/01 - InformaticaMathematics - History and OverviewApplied MathematicsSettore MAT/04 - Matematiche ComplementariMultimedia (cs.MM)Gestural similarity Gestalt diagrams Dirac notation sonificationComputational MathematicsdiagramsSonificationModeling and SimulationGestalt psychologyDirac notationInformationSystems_MISCELLANEOUSSettore ING-INF/05 - Sistemi di Elaborazione delle InformazioniComputer Science - MultimediaMusic
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Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI

2015

Objectives: We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. Methods: The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two in…

FOS: Computer and information sciencesgranger causality (GC)Multivariate statisticsComputer scienceRestComputer Science - Information TheoryBiomedical EngineeringsynergyFOS: Physical sciencescomputer.software_genre01 natural sciences03 medical and health sciences0302 clinical medicineGranger causality0103 physical sciencesConnectomeRedundancy (engineering)HumansBrain connectivityTime series010306 general physicsModels StatisticalHuman Connectome ProjectResting state fMRIredundancybusiness.industryInformation Theory (cs.IT)functional magnetic resonance imaging (fMRI)BrainPattern recognitionComplex networkMagnetic Resonance ImagingVariable (computer science)Physics - Data Analysis Statistics and ProbabilityQuantitative Biology - Neurons and CognitionFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPairwise comparisonNeurons and Cognition (q-bio.NC)Artificial intelligenceData miningNerve Netbusinesscomputer030217 neurology & neurosurgeryData Analysis Statistics and Probability (physics.data-an)
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Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…

2022

Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…

FOS: Computer and information sciencesmultivariate time seriesPhysiologyEntropyRespirationBiomedical EngineeringBiophysicsheart rate variabilitytransfer entropyredundancy and synergyBlood PressureHeartQuantitative Biology - Quantitative MethodsCardiovascular SystemMethodology (stat.ME)Heart RatePhysiology (medical)FOS: Biological sciencesCardiovascular controlSettore ING-INF/06 - Bioingegneria Elettronica E Informaticavector autoregressive fractionally integrated (VARFI) modelsHumansQuantitative Methods (q-bio.QM)Statistics - MethodologyPhysiological measurement
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A multi-layer method to study genome-scale positions of nucleosomes

2009

AbstractThe basic unit of eukaryotic chromatin is the nucleosome, consisting of about 150 bp of DNA wrapped around a protein core made of histone proteins. Nucleosomes position is modulated in vivo to regulate fundamental nuclear processes. To measure nucleosome positions on a genomic scale both theoretical and experimental approaches have been recently reported. We have developed a new method, Multi-Layer Model (MLM), for the analysis of nucleosome position data obtained with microarray-based approach. The MLM is a feature extraction method in which the input data is processed by a classifier to distinguish between several kinds of patterns. We applied our method to simulated-synthetic and…

Feature extractionNucleosome positioningGenomicsSaccharomyces cerevisiaeComputational biologyHidden Markov Modelchemistry.chemical_compoundSettore BIO/10 - BiochimicaNucleosome positioning Hidden Markov Model Classification Multi-layer methodGeneticsHumansNucleosomeMulti-layer methodHidden Markov modelBase PairingMulti layerOligonucleotide Array Sequence AnalysisGeneticsBase SequenceSettore INF/01 - InformaticabiologyGenome HumanClassificationMarkov ChainsNucleosomesChromatinHistonechemistrybiology.proteinDNAGenomics
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Assessing causality in brain dynamics and cardiovascular control

2013

Understanding how different cerebral areas interact to produce an integrated behaviour and disentangling the mechanisms that contribute to cardiovascular control are two of the major challenges of brain and cardiovascular neuroscience. The increasing availability of simultaneous continuous

Feedback PhysiologicalCognitive scienceIntroductionComputer scienceGeneral MathematicsGeneral EngineeringBrainGeneral Physics and AstronomyHeartCardiovascular controlModels BiologicalCausality (physics)EngineeringPhysics and AstronomyMathematics; Engineering; Physics and AstronomySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaAnimalsHumansComputer SimulationNerve NetAlgorithmsMathematic
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Local electrical characterisation of human atrial fibrillation

2002

The rate of success of radio-frequency catheter ablation in the treatment of atrial fibrillation may be significantly improved by evaluating the local electrical properties of the atrial tissue. The aim of this study is the development of an automatic procedure for the characterisation of the local electrical activity during atrial fibrillation and the comparison of its performance with the manual analysis. The adopted procedures were the semi-automatic measurement of the local fibrillation intervals (A-A intervals) and the manual electrogram classification following the criteria suggested by Wells (1978) or Konings (1997). Two methods have been used: Principal Component Analysis and Cluste…

Fibrillationmedicine.medical_specialtymedicine.diagnostic_testbusiness.industrymedicine.medical_treatmentComputer Science Applications1707 Computer Vision and Pattern RecognitionAtrial fibrillationCatheter ablationAtrial tissuemedicine.diseaseInternal medicineSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaClinical valueCardiologyMedicinemedicine.symptomCardiology and Cardiovascular MedicinebusinessElectrocardiographyComputers in Cardiology 2000. Vol.27 (Cat. 00CH37163)
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Resource-efficient hardware implementation of a neural-based node for automatic fingerprint classification

2017

Modern mobile communication networks and Internet of Things are paving the way to ubiquitous and mobile computing. On the other hand, several new computing paradigms, such as edge computing, demand for high computational capabilities on specific network nodes. Ubiquitous environments require a large number of distributed user identification nodes enabling a secure platform for resources, services and information management. Biometric systems represent a useful option to the typical identification systems. An accurate automatic fingerprint classification module provides a valuable indexing scheme that allows for effective matching in large fingerprint databases. In this work, an efficient em…

Fingerprint classificationField programmable gate array (FPGA)INF/01 - INFORMATICAWeightless neural networkWeightless neural networksMobile and ubiquitous ComputingField programmable gate array (FPGA); Fingerprint classification; Mobile and ubiquitous Computing; Virtual neuron; Weightless neural networksVirtual neuronMobile and Ubiquitous Computing Fingerprint Classification Weightless Neural Net- works Virtual Neuron Field Programmable Gate Array (FPGA)
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Ambiguity and complementation in recognizable two-dimensional languages

2008

The theory of one-dimensional (word) languages is well founded and investigated since fifties. From several years, the increasing interest for pattern recognition and image processing motivated the research on two-dimensional or picture languages, and nowadays this is a research field of great interest. A first attempt to formalize the concept of finite state recognizability for two-dimensional languages can be attributed to Blum and Hewitt ([7]) who started in 1967 the study of finite state devices that can define two-dimensional languages, with the aim to finding a counterpart of what regular languages are in one dimension. Since then, many approaches have been presented in the literature…

Finite-state machineTessellationCOMPLEXITYSettore INF/01 - Informaticamedia_common.quotation_subjectPicture LanguageAmbiguityPattern RecognitionPicture languageAlgebraRule-based machine translationRegular languageFormal LanguagePICTURE-LANGUAGES; NONDETERMINISM; COMPLEXITY; AUTOMATAFormal languageRegular expressionAUTOMATAArithmeticPICTURE-LANGUAGESmedia_commonMathematicsNONDETERMINISM
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A genetic algorithm for image segmentation

2002

The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.

Fitness functionSettore INF/01 - Informaticabusiness.industrySegmentation-based object categorizationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionImage segmentationReal imageMinimum spanning tree-based segmentationComputer Science::Computer Vision and Pattern RecognitionGenetic algorithmComputer visionSegmentationArtificial intelligencebusinessGenetic algorithm Image SegmentationMathematics
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