Search results for " Probability"

showing 10 items of 2176 documents

The adaptive value of tandem communication in ants:Insights from an agent-based model

2021

AbstractSocial animals often share information about the location of resources, such as a food source or a new nest-site. One well-studied communication strategy in ants is tandem running, whereby a leader guides a recruit to a resource. Tandem running is considered an example of animal teaching because a leader adjusts her behaviour and invests time to help another ant to learn the location of a resource more efficiently. Tandem running also has costs, such as waiting inside the nest for a leader and a reduced walking speed. Whether and when these costs outweigh the benefits of tandem running is not well understood. We developed an agent-based simulation model to investigate the conditions…

0301 basic medicineStatistics and ProbabilityForage (honey bee)Adaptive valueOperations researchComputer scienceForagingGeneral Biochemistry Genetics and Molecular BiologyRunning03 medical and health sciences0302 clinical medicineResource (project management)NestAnimalsLearningAgent-based modelGeneral Immunology and MicrobiologyTandemAntsCommunicationApplied MathematicsGeneral MedicineBeesVariable (computer science)030104 developmental biologyModeling and SimulationSocial animalFemaleGeneral Agricultural and Biological Sciences030217 neurology & neurosurgeryTandem running
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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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A generalization of Kingman's model of selection and mutation and the Lenski experiment.

2017

Kingman’s model of selection and mutation studies the limit type value distribution in an asexual population of discrete generations and infinite size undergoing selection and mutation. This paper generalizes the model to analyze the long-term evolution of Escherichia. coli in Lenski experiment. Weak assumptions for fitness functions are proposed and the mutation mechanism is the same as in Kingman’s model. General macroscopic epistasis are designable through fitness functions. Convergence to the unique limit type distribution is obtained.

0301 basic medicineStatistics and ProbabilityGeneralizationPopulationBiology01 natural sciencesModels BiologicalGeneral Biochemistry Genetics and Molecular Biology010104 statistics & probability03 medical and health sciencesStatisticsEscherichia coliApplied mathematicsQuantitative Biology::Populations and EvolutionLimit (mathematics)0101 mathematicsSelection GeneticeducationSelection (genetic algorithm)education.field_of_studyFitness functionGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineQuantitative Biology::GenomicsBiological Evolution030104 developmental biologyDistribution (mathematics)Modeling and SimulationMutation (genetic algorithm)MutationEpistasisGeneral Agricultural and Biological SciencesMathematical biosciences
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Nature lessons: the whitefly bacterial endosymbiont is a minimal amino acid factory with unusual energetics

2016

Reductive genome evolution is a universal phenomenon observed in endosymbiotic bacteria in insects. As the genome reduces its size and irreversibly losses coding genes, the functionalities of the cell system, including the energetics processes, are more restricted. Several energetic pathways can also be lost. How do these reduced metabolic networks sustain the energy needs of the system? Among the bacteria with reduced genomes Candidatus Portiera aleyrodidarum, obligate endosymbiont of whiteflies, represents an extreme case since lacks several key mechanisms for ATP generation. Thus, to analyze the cell energetics in this system, a genome-scale metabolic model of this endosymbiont was const…

0301 basic medicineStatistics and ProbabilityGenome evolutionAnabolismSystems biology030106 microbiologyCell EnergeticsBiologyModels BiologicalGenomeGeneral Biochemistry Genetics and Molecular BiologyHemiptera03 medical and health sciencesMetabolic flux analysisAnimalsAmino AcidsSymbiosisGeneGenome sizeCarotenoidchemistry.chemical_classificationGeneral Immunology and MicrobiologyObligateApplied MathematicsEnergeticsGeneral MedicineMetabolismbeta Carotenebiology.organism_classificationMetabolic Flux AnalysisAmino acidHalomonadaceae030104 developmental biologychemistryBiochemistryModeling and SimulationEnergy MetabolismGeneral Agricultural and Biological SciencesGenome BacterialMetabolic Networks and PathwaysBacteria
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The latent geometry of the human protein interaction network

2017

Abstract Motivation A series of recently introduced algorithms and models advocates for the existence of a hyperbolic geometry underlying the network representation of complex systems. Since the human protein interaction network (hPIN) has a complex architecture, we hypothesized that uncovering its latent geometry could ease challenging problems in systems biology, translating them into measuring distances between proteins. Results We embedded the hPIN to hyperbolic space and found that the inferred coordinates of nodes capture biologically relevant features, like protein age, function and cellular localization. This means that the representation of the hPIN in the two-dimensional hyperboli…

0301 basic medicineStatistics and ProbabilityGeometric analysisComputer scienceHyperbolic geometrySystems biologyComplex systemContext (language use)GeometryBiochemistryProtein–protein interaction03 medical and health sciencesInteraction networkHumansProtein Interaction MapsRepresentation (mathematics)Cluster analysisMolecular BiologySystems BiologyHyperbolic spaceProteinsFunction (mathematics)Original PapersComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicsEmbeddingSignal transductionAlgorithmsSignal Transduction
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A deterministic model for highly contagious diseases: The case of varicella

2016

[EN] The classic nonlinear Kermack-McKendrick model based upon a system of differential equations has been widely applied to model the rise and fall of global pandemic and also seasonal epidemic by introducing a forced harmonic infectivity which would change throughout the year. These methods work well in their respective domains of applicability, and for certain diseases, but they fail when both seasonality and high infectivity are combined. In this paper we consider a Susceptible-Infected-Recovered, or SIR, model with two latent states to model the propagation and evolutionary history of varicella in humans. We show that infectivity can be calculated from real data and we find a nonstanda…

0301 basic medicineStatistics and ProbabilityInfectivity030106 microbiologyBiologyHighly contagious diseasesInfectivity evolutionCondensed Matter PhysicsVaricella03 medical and health sciences0302 clinical medicineSystem of differential equationsPandemicEconometrics030212 general & internal medicineMATEMATICA APLICADACompartmental models
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panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data.

2018

Abstract Motivation The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data. Results PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic spec…

0301 basic medicineStatistics and ProbabilityLineage (genetic)Computer scienceAb initioComputational biologyBacterial genome size[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]BiochemistryGenome[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]Insertion sequenceMolecular BiologyGenomic organizationHigh-Throughput Nucleotide SequencingSequence Analysis DNA[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/BacteriologyPipeline (software)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and Mathematics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]DNA Transposable Elements[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Genome BacterialSoftwareBioinformatics (Oxford, England)
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Mathematical investigation of innate immune responses to lung cancer: The role of macrophages with mixed phenotypes

2021

Abstract Macrophages’ role in the evolution of solid tumours is a well accepted fact, with the M1-like macrophages having an anti-tumour role and the M2-like macrophages having a pro-tumour role. Despite the fact that some clinical studies on lung tumours have emphasised also the presence of macrophages with mixed M1 and M2 phenotypes in addition to macrophages with distinct phenotypes, the majority of studies still use the distinct M1-M2 classification to predict the evolution of tumours and patient survival. In this theoretical study we use a mathematical modelling and computational approach to investigate the role of macrophages with mixed phenotype on growth/control/elimination of lung …

0301 basic medicineStatistics and ProbabilityLung Neoplasms[SDV]Life Sciences [q-bio]BiologyGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciences0302 clinical medicinemedicineMacrophageHumans[NLIN]Nonlinear Sciences [physics][MATH]Mathematics [math]Lung cancerComputingMilieux_MISCELLANEOUSInnate immune systemGeneral Immunology and MicrobiologyApplied MathematicsMacrophagesPatient survivalGeneral MedicineModels Theoreticalmedicine.diseasePhenotypeImmunity Innate030104 developmental biologyPhenotypeModeling and SimulationCancer researchLung tumoursGeneral Agricultural and Biological Sciences030217 neurology & neurosurgery
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Variance component analysis to assess protein quantification in biomarker discovery. Application to MALDI-TOF mass spectrometry.

2017

International audience; Controlling the technological variability on an analytical chain is critical for biomarker discovery. The sources of technological variability should be modeled, which calls for specific experimental design, signal processing, and statistical analysis. Furthermore, with unbalanced data, the various components of variability cannot be estimated with the sequential or adjusted sums of squares of usual software programs. We propose a novel approach to variance component analysis with application to the matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) technology and use this approach for protein quantification by a classical signal processing algori…

0301 basic medicineStatistics and ProbabilityMALDI-TOFexperimental designBiometryprotein quantificationQuantitative proteomicsVariance component analysis[ CHIM ] Chemical Sciences01 natural sciencesSignaltechnological variability010104 statistics & probability03 medical and health sciencesstatistical analysis[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[CHIM.ANAL]Chemical Sciences/Analytical chemistryComponent (UML)[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]biomarker discoverysum of squares type0101 mathematicsBiomarker discoverysignal processingMathematicsSignal processingAnalysis of Variance[ PHYS ] Physics [physics]Noise (signal processing)ProteinsGeneral MedicineVariance (accounting)[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]030104 developmental biologySpectrometry Mass Matrix-Assisted Laser Desorption-IonizationLinear Modelsvariance components[ CHIM.ANAL ] Chemical Sciences/Analytical chemistryStatistics Probability and UncertaintyBiological systemAlgorithmsBiomarkersBiometrical journal. Biometrische Zeitschrift
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A heuristic, iterative algorithm for change-point detection in abrupt change models

2017

Change-point detection in abrupt change models is a very challenging research topic in many fields of both methodological and applied Statistics. Due to strong irregularities, discontinuity and non-smootheness, likelihood based procedures are awkward; for instance, usual optimization methods do not work, and grid search algorithms represent the most used approach for estimation. In this paper a heuristic, iterative algorithm for approximate maximum likelihood estimation is introduced for change-point detection in piecewise constant regression models. The algorithm is based on iterative fitting of simple linear models, and appears to extend easily to more general frameworks, such as models i…

0301 basic medicineStatistics and ProbabilityMathematical optimizationIterative methodHeuristic (computer science)Linear model01 natural sciencesPiecewise constant model Approximate maximum likelihood Model linearization Grid search limitations010104 statistics & probability03 medical and health sciencesComputational MathematicsDiscontinuity (linguistics)030104 developmental biologyHyperparameter optimizationCovariatePiecewise0101 mathematicsStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaChange detectionMathematics
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