Search results for "Mathematic"

showing 10 items of 24974 documents

Uhlmann number in translational invariant systems

2019

We define the Uhlmann number as an extension of the Chern number, and we use this quantity to describe the topology of 2D translational invariant Fermionic systems at finite temperature. We consider two paradigmatic systems and we study the changes in their topology through the Uhlmann number. Through the linear response theory we linked two geometrical quantities of the system, the mean Uhlmann curvature and the Uhlmann number, to directly measurable physical quantities, i.e. the dynamical susceptibility and to the dynamical conductivity, respectively.

0301 basic medicineSettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciMathematics::Analysis of PDEsFOS: Physical scienceslcsh:MedicineCurvatureArticleCondensed Matter - Strongly Correlated Electrons03 medical and health sciences0302 clinical medicineTopological insulatorsInvariant (mathematics)lcsh:ScienceCondensed Matter - Statistical MechanicsMathematicsMathematical physicsPhysical quantityQuantum PhysicsMultidisciplinaryChern classStatistical Mechanics (cond-mat.stat-mech)Strongly Correlated Electrons (cond-mat.str-el)lcsh:RUhlmann number Chern number 2D topological Fermionic systems finite temperature dynamical susceptibility dynamical conductivity030104 developmental biologylcsh:QQuantum Physics (quant-ph)Theoretical physicsLinear response theory030217 neurology & neurosurgeryScientific Reports
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Block Sorting-Based Transformations on Words: Beyond the Magic BWT

2018

The Burrows-Wheeler Transform (BWT) is a word transformation introduced in 1994 for Data Compression and later results have contributed to make it a fundamental tool for the design of self-indexing compressed data structures. The Alternating Burrows-Wheeler Transform (ABWT) is a more recent transformation, studied in the context of Combinatorics on Words, that works in a similar way, using an alternating lexicographical order instead of the usual one. In this paper we study a more general class of block sorting-based transformations. The transformations in this new class prove to be interesting combinatorial tools that offer new research perspectives. In particular, we show that all the tra…

0301 basic medicineSettore INF/01 - InformaticaComputer scienceData_CODINGANDINFORMATIONTHEORY0102 computer and information sciencesBlock sortingData structureLexicographical order01 natural sciencesUpper and lower bounds03 medical and health sciencesCombinatorics on words030104 developmental biology010201 computation theory & mathematicsArithmeticCompressed Data Structures Block Sorting Combinatorics on Words AlgorithmsData compression
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Ecological network analysis reveals the inter-connection between soil biodiversity and ecosystem function as affected by land use across Europe

2016

Soil organisms are considered drivers of soil ecosystem services (primary productivity, nutrient cycling, carbon cycling, water regulation) associated with sustainable agricultural production. Soil biodiversity was highlighted in the soil thematic strategy as a key component of soil quality. The lack of quantitative standardised data at a large scale has resulted in poor understanding of how soil biodiversity could be incorporated into legislation for the protection of soil quality. In 2011, the EcoFINDERS (FP7) project sampled 76 sites across 11 European countries, covering five biogeographical zones (Alpine, Atlantic, Boreal, Continental and Mediterranean) and three land-uses (arable, gra…

0301 basic medicineSoil biodiversityNitrogenSoil biology[SDV]Life Sciences [q-bio]DIVERSITYSoil ScienceCarbon cycling and storageWiskundige en Statistische Methoden - BiometrisNutrient cyclingARBUSCULAR MYCORRHIZAL FUNGIFOOD WEBS03 medical and health sciencesFOREST SOILCARBON SEQUESTRATIONSoil functionsSoil ecologyQUALITYMICROBIAL COMMUNITIESMathematical and Statistical Methods - BiometrisBodembiologie2. Zero hungerSoil healthEcologyEcologySoil organic matterUSE SYSTEMSPhosphorus04 agricultural and veterinary sciencesSoil carbonSoil Biology15. Life on landPE&RCAgricultural and Biological Sciences (miscellaneous)Soil qualitySoil biodiversityTERRESTRIAL ECOSYSTEMS030104 developmental biologyAgronomyinternational040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceEXTRACELLULAR ENZYME-ACTIVITIESEcosystem functionNetwork analysis
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SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations

2016

Various approaches to calling single-nucleotide variants (SNVs) or insertion-or-deletion (indel) mutations have been developed based on next-generation sequencing (NGS). However, most of them are dedicated to a particular type of mutation, e.g. germline SNVs in normal cells, somatic SNVs in cancer/tumor cells, or indels only. In the literature, efficient and integrated callers for both germline and somatic SNVs/indels have not yet been extensively investigated. We present SNVSniffer, an efficient and integrated caller identifying both germline and somatic SNVs/indels from NGS data. In this algorithm, we propose the use of Bayesian probabilistic models to identify SNVs and investigate a mult…

0301 basic medicineSomatic cellBayesian probabilityBiologyPolymorphism Single NucleotideGermline03 medical and health sciencesGene FrequencyINDEL MutationStructural BiologyModelling and SimulationIndel callingGenetic variationHumansAlleleIndelMolecular BiologyOvarian NeoplasmsGeneticsResearchApplied MathematicsComputational BiologyHigh-Throughput Nucleotide SequencingSNP callingSomatic SNV callingCystadenocarcinoma SerousComputer Science ApplicationsGerm Cells030104 developmental biologyBayesian modelModeling and SimulationMutation (genetic algorithm)FemaleMultinomial distributionAlgorithmsBMC Systems Biology
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Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony

2016

In this paper, we study neuronal network analysis based on microelectrode measurements. We search for potential relations between time correlated changes in spectral distributions and synchrony for neuronal network activity. Spectral distribution is quantified by spectral entropy as a measure of uniformity/complexity and this measure is calculated as a function of time for the recorded neuronal signals, i.e., time variant spectral entropy. Time variant correlations in the spectral distributions between different parts of a neuronal network, i.e., of concurrent measurements via different microelectrodes, are calculated to express the relation with a single scalar. We demonstrate these relati…

0301 basic medicineSpectral power distributionhippocampusta3112Correlation03 medical and health sciences0302 clinical medicineStatisticsBiological neural networkAnimalsEntropy (information theory)Neuronal synchronyAnalysis methodMathematicsta217Quantitative Biology::Neurons and Cognitionta213Spectral entropybiological neural networkselectrodesrats030104 developmental biologycorrelationBiological systementropyprobesMicroelectrodes030217 neurology & neurosurgery
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Multiple steady states and the form of response functions to antigen in a model for the initiation of T cell activation

2017

The aim of this paper is to study the qualitative behaviour predicted by a mathematical model for the initial stage of T-cell activation. The state variables in the model are the concentrations of phosphorylation states of the T-cell receptor (TCR) complex and the phosphatase SHP-1 in the cell. It is shown that these quantities cannot approach zero and that the model possesses more than one positive steady state for certain values of the parameters. It can also exhibit damped oscillations. It is proved that the chemical concentration which represents the degree of activation of the cell, that of the maximally phosphorylated form of the TCR complex, is, in general, a non-monotone function of…

0301 basic medicineState variable1004T cellMolecular Networks (q-bio.MN)PhosphatasemultistationarityDynamical Systems (math.DS)24Dissociation (chemistry)immunology03 medical and health sciences119medicineFOS: Mathematics1008Quantitative Biology - Molecular NetworksMathematics - Dynamical Systemslcsh:ScienceReceptort cellsMultidisciplinaryChemistryT-cell receptor92C37Dissociation constant030104 developmental biologymedicine.anatomical_structureFOS: Biological sciencesBiophysicsPhosphorylationlcsh:QMathematicsResearch Article
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Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies

2016

Mieth, Bettina et al.

0301 basic medicineStatistical methodsComputer scienceGenome-wide association studyMachine learningcomputer.software_genreGenome-wide association studiesStatistical powerArticle[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Set (abstract data type)03 medical and health sciences[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]10007 Department of EconomicsStatistical significanceReplication (statistics)genomeStatistical hypothesis testingGenetic association1000 MultidisciplinaryMultidisciplinarybusiness.industryComputational scienceInstitut für Mathematik330 EconomicsSupport vector machine030104 developmental biologyMultiple comparisons problemwide association studiesstatistical methodsArtificial intelligencebusinesscomputer
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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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Two-Stage Bayesian Approach for GWAS With Known Genealogy

2019

Genome-wide association studies (GWAS) aim to assess relationships between single nucleotide polymorphisms (SNPs) and diseases. They are one of the most popular problems in genetics, and have some peculiarities given the large number of SNPs compared to the number of subjects in the study. Individuals might not be independent, especially in animal breeding studies or genetic diseases in isolated populations with highly inbred individuals. We propose a family-based GWAS model in a two-stage approach comprising a dimension reduction and a subsequent model selection. The first stage, in which the genetic relatedness between the subjects is taken into account, selects the promising SNPs. The se…

0301 basic medicineStatistics and ProbabilityBayesian probabilityPopulationSingle-nucleotide polymorphismGenome-wide association studyComputational biologyEstadísticaBiologyKinship coefficientModel selection01 natural sciencesBeta-thalassemia010104 statistics & probability03 medical and health sciencesBeta-thalassemia disorderModelsRobust prior distributionRegularizationDiscrete Mathematics and Combinatorics0101 mathematicsStage (cooking)Genetic associationGenome-wide associationModel selectionVariable-selectionProbability and statisticsBayes factorRegressionBayes factor030104 developmental biologyPhenotypeStatistics Probability and UncertaintyGaussian Markov random field
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Stagewise pseudo-value regression for time-varying effects on the cumulative incidence

2015

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event s…

0301 basic medicineStatistics and ProbabilityCarcinoma HepatocellularTime FactorsEpidemiologyComputer scienceFeature selectionBiostatistics01 natural sciences010104 statistics & probability03 medical and health sciencesRisk FactorsStatisticsCovariateEconometricsHumansComputer SimulationCumulative incidenceRegistries0101 mathematicsEvent (probability theory)Models StatisticalIncidenceLiver NeoplasmsAbsolute risk reductionRegression analysisRegression030104 developmental biologyRegression AnalysisJackknife resamplingAlgorithmsStatistics in Medicine
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