Search results for " data analysis"

showing 10 items of 231 documents

Metabolic flux understanding of Pichia pastoris grown on heterogenous culture media

2014

[EN] Within the emergent field of Systems Biology, mathematical models obtained from physical chemical laws (the so-called first principles-based models) of microbial systems are employed to discern the principles that govern cellular behaviour and achieve a predictive understanding of cellular functions. The reliance on this biochemical knowledge has the drawback that some of the assumptions (specific kinetics of the reaction system, unknown dynamics and values of the model parameters) may not be valid for all the metabolic possible states of the network. In this uncertainty context, the combined use of fundamental knowledge and data measured in the fermentation that describe the behaviour…

Principal Component AnalysisbiologyMathematical modelManufacturing processComputer scienceProcess Chemistry and TechnologySystems biologyMonte Carlo samplingESTADISTICA E INVESTIGACION OPERATIVACellular functionsMetabolic networkMetabolic networkMissing-data methods for Exploratory Data AnalysisContext (language use)biology.organism_classificationINGENIERIA DE SISTEMAS Y AUTOMATICAComputer Science ApplicationsAnalytical ChemistryPichia pastorisEconometricsBiochemical engineeringPossibilistic consistency analysisFlux (metabolism)SpectroscopySoftware
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Reinterpretation of Classic Proton Charge Form Factor Measurements

2020

In 1963, a proton radius of $0.805(11)~\mathrm{fm}$ was extracted from electron scattering data and this classic value has been used in the standard dipole parameterization of the form factor. In trying to reproduce this classic result, we discovered that there was a sign error in the original analysis and that the authors should have found a value of $0.851(19)~\mathrm{fm}$. We additionally made use of modern computing power to find a robust function for extracting the radius using this 1963 data's spacing and uncertainty. This optimal function, the Pad\'{e} $(0,1)$ approximant, also gives a result which is consistent with the modern high precision proton radius extractions.

ProtonMaterials Science (miscellaneous)BiophysicsFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciences0103 physical sciencesPadé approximantNuclear Experiment (nucl-ex)Physical and Theoretical Chemistry010306 general physicsform factorsNuclear ExperimentMathematical PhysicsPhysicsForm factor (quantum field theory)Function (mathematics)Radiuslcsh:QC1-999Computational physicsDipolecharge radiuselectron scatteringPhysics - Data Analysis Statistics and Probabilitystatistical methodsElectron scatteringlcsh:PhysicsData Analysis Statistics and Probability (physics.data-an)protonSign (mathematics)Frontiers in Physics
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Quantitative and qualitative analysis of the mental models deployed by undergraduate students in explaining thermally activated phenomena

2017

In this contribution we describe a research aimed at pointing out the quality of mental models undergraduate engineering students deploy when asked to create explanations for phenomena/processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are initially analyzed using researcher-generated categories of reasoning, based on the Physics Education Research literature on student understanding of the relevant physics content. The inferred students’ mental models about the analyzed phenomena are categorized as practical, descriptive, or explanatory, based on an analysis of student responses to the questionnaire. A qualitative analysi…

Pulmonary and Respiratory MedicineResearch literatureQuantitative analysimedia_common.quotation_subjectSettore FIS/08 - Didattica E Storia Della Fisica05 social sciencesPhysics education050301 educationContext (language use)qualitative analysimental modelsQualitative analysisQuantitative analysis (finance)Pediatrics Perinatology and Child HealthMathematics educationComputingMilieux_COMPUTERSANDEDUCATIONQuality (business)Undergraduate engineeringmental models quantitative data analysisPsychologylcsh:L0503 educationmedia_commonlcsh:Education
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GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

2021

AbstractBackgroundThe interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats - normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently.ResultsWe developed the GeneTonic software package, whi…

QH301-705.5Process (engineering)Computer scienceShinyComputer applications to medicine. Medical informaticsBioconductor610 MedizinR858-859.7Context (language use)Interactive data analysisReproducible researchBioconductorInteractivity610 Medical sciencesUse caseRNA-SeqBiology (General)MIT LicenseTranscriptomicsInformation retrievalBase SequenceSequence Analysis RNAData interpretationData visualizationRReproducibility of ResultsIdentification (information)WorkflowRNASoftwareFunctional enrichment analysis
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Feature selection on a dataset of protein families: from exploratory data analysis to statistical variable importance

2016

Proteins are characterized by several typologies of features (structural, geometrical, energy). Most of these features are expected to be similar within a protein family. We are interested to detect which features can identify proteins that belong to a family, as well as to define the boundaries among families. Some features are redundant: they could generate noise in identifying which variables are essential as a fingerprint and, consequently, if they are related or not to a function of a protein family. We defined an original approach to analyze protein features for defining their relationships and peculiarities within protein families. A multistep approach has been mainly performed in R …

Quantitative Biology::Biomoleculesbusiness.industrySparse PCAPattern recognitionFeature selectionLinear discriminant analysisCross-validationRandom forestExploratory data analysisStatistical classificationArtificial intelligencebusinessCluster analysisMathematics
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Investigating the quality of mental models deployed by undergraduate engineering students in creating explanations: The case of thermally activated p…

2013

This paper describes a method aimed at pointing out the quality of the mental models undergraduate engineering students deploy when asked to create explanations for phenomena or processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are quantitatively analyzed using researcher-generated categories of reasoning, based on the physics education research literature on student understanding of the relevant physics content. The use of statistical implicative analysis tools allows us to successfully identify clusters of students with respect to the similarity to the reasoning categories, defined as ``practical or everyday,'' ``descri…

Quantitative data analysiQualitative data analysisPhysics educationLC8-6691Learning environmentmedia_common.quotation_subjectMultimethodologySettore FIS/08 - Didattica E Storia Della FisicaPhysicsQC1-999Physics educationGeneral Physics and AstronomyContext (language use)Special aspects of educationEducationConsistency (negotiation)Engineering educationSimilarity (psychology)Mathematics educationQuality (business)Psychologymedia_commonPhysical Review Special Topics. Physics Education Research
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Observation of time-invariant coherence in a room temperature quantum simulator

2015

The ability to live in coherent superpositions is a signature trait of quantum systems and constitutes an irreplaceable resource for quantum-enhanced technologies. However, decoherence effects usually destroy quantum superpositions. It has been recently predicted that, in a composite quantum system exposed to dephasing noise, quantum coherence in a transversal reference basis can stay protected for indefinite time. This can occur for a class of quantum states independently of the measure used to quantify coherence, and requires no control on the system during the dynamics. Here, such an invariant coherence phenomenon is observed experimentally in two different setups based on nuclear magnet…

Quantum PhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsPhysics - Data Analysis Statistics and ProbabilityMesoscale and Nanoscale Physics (cond-mat.mes-hall)FOS: Physical sciencesNuclear Experiment (nucl-ex)Quantum Physics (quant-ph)Nuclear ExperimentData Analysis Statistics and Probability (physics.data-an)
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Negative Probabilities and Contextuality

2015

There has been a growing interest, both in physics and psychology, in understanding contextuality in experimentally observed quantities. Different approaches have been proposed to deal with contextual systems, and a promising one is contextuality-by-default, put forth by Dzhafarov and Kujala. The goal of this paper is to present a tutorial on a different approach: negative probabilities. We do so by presenting the overall theory of negative probabilities in a way that is consistent with contextuality-by-default and by examining with this theory some simple examples where contextuality appears, both in physics and psychology.

Quantum PhysicsPhysics - Data Analysis Statistics and ProbabilityFOS: Physical sciencesQuantum Physics (quant-ph)Data Analysis Statistics and Probability (physics.data-an)
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From time series to complex networks: the visibility graph

2008

In this work we present a simple and fast computational method, the visibility algorithm , that converts a time series into a graph. The constructed graph inherits several properties of the series in its structure. Thereby, periodic series convert into regular graphs, and random series do so into random graphs. Moreover, fractal series convert into scale-free networks, enhancing the fact that power law degree distributions are related to fractality, something highly discussed recently. Some remarkable examples and analytical tools are outlined to test the method's reliability. Many different measures, recently developed in the complex network theory, could by means of this new approach cha…

Random graphMultidisciplinaryTheoretical computer scienceComputer scienceVisibility graphComplex systemFOS: Physical sciencesProbability and statisticsComplex network01 natural sciences010305 fluids & plasmasFractalVisibility graph analysisPhysics - Data Analysis Statistics and Probability0103 physical sciencesPhysical Sciences010306 general physicsData Analysis Statistics and Probability (physics.data-an)Brownian motion
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Bayesian Analysis of a Future Beta Decay Experiment's Sensitivity to Neutrino Mass Scale and Ordering

2021

Bayesian modeling techniques enable sensitivity analyses that incorporate detailed expectations regarding future experiments. A model-based approach also allows one to evaluate inferences and predicted outcomes, by calibrating (or measuring) the consequences incurred when certain results are reported. We present procedures for calibrating predictions of an experiment's sensitivity to both continuous and discrete parameters. Using these procedures and a new Bayesian model of the $\beta$-decay spectrum, we assess a high-precision $\beta$-decay experiment's sensitivity to the neutrino mass scale and ordering, for one assumed design scenario. We find that such an experiment could measure the el…

Semileptonic decaydata analysis methodParticle physicsBayesian probabilityFOS: Physical sciences[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]Bayesian inferenceBayesian01 natural sciencesMeasure (mathematics)statistics: Bayesianmass: scaleHigh Energy Physics - Phenomenology (hep-ph)0103 physical sciencesCalibrationneutrino: massSensitivity (control systems)Nuclear Experiment (nucl-ex)010306 general physicsNuclear ExperimentPhysics010308 nuclear & particles physicsElectroweak InteractionProbability and statisticssemileptonic decaycalibrationsensitivityneutrino: nuclear reactorHigh Energy Physics - Phenomenologymass: calibration[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]Physics - Data Analysis Statistics and ProbabilityspectralHigh Energy Physics::ExperimentNeutrinoData Analysis Statistics and Probability (physics.data-an)[PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis Statistics and Probability [physics.data-an]Symmetries
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