Search results for "Quantitative Biology::Genomics"

showing 10 items of 39 documents

Measuring the clustering effect of BWT via RLE

2017

Abstract The Burrows–Wheeler Transform (BWT) is a reversible transformation on which are based several text compressors and many other tools used in Bioinformatics and Computational Biology. The BWT is not actually a compressor, but a transformation that performs a context-dependent permutation of the letters of the input text that often create runs of equal letters (clusters) longer than the ones in the original text, usually referred to as the “clustering effect” of BWT. In particular, from a combinatorial point of view, great attention has been given to the case in which the BWT produces the fewest number of clusters (cf. [5] , [16] , [21] , [23] ). In this paper we are concerned about t…

0301 basic medicineGeneral Computer SciencePermutationComputer Science (all)Binary number0102 computer and information sciencesQuantitative Biology::Genomics01 natural sciencesUpper and lower boundsTheoretical Computer ScienceCombinatorics03 medical and health sciencesPermutation030104 developmental biologyTransformation (function)BWT010201 computation theory & mathematicsRun-length encodingComputer Science::Data Structures and AlgorithmsCluster analysisPrimitive root modulo nBWT; Permutation; Run-length encoding; Theoretical Computer Science; Computer Science (all)Word (computer architecture)Run-length encodingMathematics
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MicroRNA Intercellular Transfer and Bioelectrical Regulation of Model Multicellular Ensembles by the Gap Junction Connectivity.

2017

We have studied theoretically the microRNA (miRNA) intercellular transfer through voltage-gated gap junctions in terms of a biophysically grounded system of coupled differential equations. Instead of modeling a specific system, we use a general approach describing the interplay between the genetic mechanisms and the single-cell electric potentials. The dynamics of the multicellular ensemble are simulated under different conditions including spatially inhomogeneous transcription rates and local intercellular transfer of miRNAs. These processes result in spatiotemporal changes of miRNA, mRNA, and ion channel protein concentrations that eventually modify the bioelectrical states of small multi…

0301 basic medicinePhysicsModels MolecularCell signalingQuantitative Biology::Molecular NetworksEnsemble averageGap junctionIon Channel ProteinGap JunctionsNanotechnologyTransfectionQuantitative Biology::GenomicsQuantitative Biology::Cell BehaviorSurfaces Coatings and FilmsCoupled differential equations03 medical and health sciencesMulticellular organismMicroRNAs030104 developmental biologymicroRNAMaterials ChemistryBiophysicsPhysical and Theoretical ChemistryIntracellularThe journal of physical chemistry. B
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KnotGenome: a server to analyze entanglements of chromosomes.

2018

Abstract The KnotGenome server enables the topological analysis of chromosome model data using three-dimensional coordinate files of chromosomes as input. In particular, it detects prime and composite knots in single chromosomes, and links between chromosomes. The knotting complexity of the chromosome is presented in the form of a matrix diagram that reveals the knot type of the entire polynucleotide chain and of each of its subchains. Links are determined by means of the Gaussian linking integral and the HOMFLY-PT polynomial. Entangled chromosomes are presented graphically in an intuitive way. It is also possible to relax structure with short molecular dynamics runs before the analysis. Kn…

0301 basic medicinePolynomialProtein ConformationGaussianPolynucleotidesBiologyType (model theory)Molecular Dynamics SimulationPrime (order theory)ChromosomesQuantitative Biology::Subcellular Processes03 medical and health sciencessymbols.namesakeMatrix (mathematics)Knot (unit)Chain (algebraic topology)GeneticsDiscrete mathematicsInternetDiagramComputational BiologyMathematics::Geometric TopologyQuantitative Biology::Genomics030104 developmental biologyWeb Server IssuesymbolsAlgorithmsSoftwareNucleic acids research
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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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Evolutionary distances corrected for purifying selection and ancestral polymorphisms.

2019

Abstract Evolutionary distance formulas that take into account effects due to ancestral polymorphisms and purifying selection are obtained on the basis of the full solution of Jukes–Cantor and Kimura DNA substitution models. In the case of purifying selection two different methods are developed. It is shown that avoiding the dimensional reduction implicitly carried out in the conventional model solving is instrumental to incorporate the quoted effects into the formalism. The problem of estimating the numerical values of the model parameters, as well as those of the correction terms, is not addressed.

0301 basic medicineStatistics and ProbabilityTime FactorsADNModel parametersGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesNegative selection0302 clinical medicineQuantitative Biology::Populations and EvolutionStatistical physicsSelection GeneticMolecular clockPhylogenyMathematicsPolymorphism GeneticGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineModels biològicsQuantitative Biology::GenomicsBiological EvolutionFormalism (philosophy of mathematics)030104 developmental biologyDimensional reductionModeling and SimulationMutationGeneral Agricultural and Biological Sciences030217 neurology & neurosurgeryEvolució (Biologia)Journal of theoretical biology
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Efficient Online Laplacian Eigenmap Computation for Dimensionality Reduction in Molecular Phylogeny via Optimisation on the Sphere

2019

Reconstructing the phylogeny of large groups of large divergent genomes remains a difficult problem to solve, whatever the methods considered. Methods based on distance matrices are blocked due to the calculation of these matrices that is impossible in practice, when Bayesian inference or maximum likelihood methods presuppose multiple alignment of the genomes, which is itself difficult to achieve if precision is required. In this paper, we propose to calculate new distances for randomly selected couples of species over iterations, and then to map the biological sequences in a space of small dimension based on the partial knowledge of this genome similarity matrix. This mapping is then used …

0303 health sciences[STAT.AP]Statistics [stat]/Applications [stat.AP]Computer scienceDimensionality reductionComputationDimension (graph theory)Complete graphMinimum spanning treeBayesian inferenceQuantitative Biology::Genomics03 medical and health sciencesComputingMethodologies_PATTERNRECOGNITION0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Algorithm030217 neurology & neurosurgeryEigenvalues and eigenvectorsDistance matrices in phylogenyComputingMilieux_MISCELLANEOUS030304 developmental biology
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Computing the Original eBWT Faster, Simpler, and with Less Memory

2021

Mantaci et al. [TCS 2007] defined the \(\mathrm {eBWT}\) to extend the definition of the \(\mathrm {BWT}\) to a collection of strings. However, since this introduction, it has been used more generally to describe any \(\mathrm {BWT}\) of a collection of strings, and the fundamental property of the original definition (i.e., the independence from the input order) is frequently disregarded. In this paper, we propose a simple linear-time algorithm for the construction of the original \(\mathrm {eBWT}\), which does not require the preprocessing of Bannai et al. [CPM 2021]. As a byproduct, we obtain the first linear-time algorithm for computing the \(\mathrm {BWT}\) of a single string that uses …

2019-20 coronavirus outbreakSpeedupString collectionsBig BWTSettore INF/01 - InformaticaSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)String (computer science)Suffix arrayOrder (ring theory)omega-orderQuantitative Biology::GenomicsBurrows-Wheeler-TransformBurrows-Wheeler-Transform String collections SAIS Big BWT prefix-free parsing extended BWTlaw.inventionCombinatoricsprefix-free parsingSimple (abstract algebra)lawSAISSAIS algorithmIndependence (probability theory)extended BWTMathematics
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Reproducing kernel hilbert spaces regression methods for genomic assisted prediction of quantitative traits.

2008

Abstract Reproducing kernel Hilbert spaces regression procedures for prediction of total genetic value for quantitative traits, which make use of phenotypic and genomic data simultaneously, are discussed from a theoretical perspective. It is argued that a nonparametric treatment may be needed for capturing the multiple and complex interactions potentially arising in whole-genome models, i.e., those based on thousands of single-nucleotide polymorphism (SNP) markers. After a review of reproducing kernel Hilbert spaces regression, it is shown that the statistical specification admits a standard mixed-effects linear model representation, with smoothing parameters treated as variance components.…

BiologyInvestigationsBayesian inferenceMachine learningcomputer.software_genreKernel principal component analysisChromosomessymbols.namesakeQuantitative Trait HeritableGeneticsAnimalsGeneticsGenomeModels GeneticRepresenter theorembusiness.industryHilbert spaceLinear modelBayes TheoremQuantitative Biology::GenomicsKernel embedding of distributionsKernel (statistics)symbolsPrincipal component regressionRegression AnalysisArtificial intelligencebusinesscomputerChickensGenetics
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Supplementary material 2 from: Pérez Santa-Rita JV, Baixeras J (2018) Two new species of Brusqeulia Razowski & Becker, 2000 from the Neotropics, with…

2018

Character matrix : Explanation note: Data matrix for phylogenetic analysis.

Brusqeulia araguensisQuantitative Biology::Quantitative MethodstaxonomyBrusqeulia yunkensisQuantitative Biology::Populations and Evolutionsubpapillar scleriteSouth AmericaEuliinasystematicsQuantitative Biology::Genomics
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CRiSPy-CUDA: Computing Species Richness in 16S rRNA Pyrosequencing Datasets with CUDA

2011

Pyrosequencing technologies are frequently used for sequencing the 16S rRNA marker gene for metagenomic studies of microbial communities. Computing a pairwise genetic distance matrix from the produced reads is an important but highly time consuming task. In this paper, we present a parallelized tool (called CRiSPy) for scalable pairwise genetic distance matrix computation and clustering that is based on the processing pipeline of the popular ESPRIT software package. To achieve high computational efficiency, we have designed massively parallel CUDA algorithms for pairwise k-mer distance and pairwise genetic distance computation. We have also implemented a memory-efficient sparse matrix clust…

CUDADistance matrixComputer scienceMetagenomicsPipeline (computing)Pairwise comparisonParallel computingCluster analysisQuantitative Biology::GenomicsMassively parallelSparse matrix
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