Search results for " Mathematics"

showing 10 items of 10797 documents

Efficient Algorithms for Sequence Analysis with Entropic Profiles

2017

Entropy, being closely related to repetitiveness and compressibility, is a widely used information-related measure to assess the degree of predictability of a sequence. Entropic profiles are based on information theory principles, and can be used to study the under-/over-representation of subwords, by also providing information about the scale of conserved DNA regions. Here, we focus on the algorithmic aspects related to entropic profiles. In particular, we propose linear time algorithms for their computation that rely on suffix-based data structures, more specifically on the truncated suffix tree (TST) and on the enhanced suffix array (ESA). We performed an extensive experimental campaign …

0301 basic medicineCompressed suffix arrayTheoretical computer scienceEntropySuffix tree0206 medical engineeringGeneralized suffix tree02 engineering and technologyString searching algorithmInformation theorylaw.invention03 medical and health scienceslawGeneticsAnimalsHumansMathematicsApplied MathematicsSuffix arrayComputational BiologyDNASequence Analysis DNAData structure030104 developmental biologySuffixAlignment free Entropy Sequence analysis Sequence comparisonAlgorithms020602 bioinformaticsBiotechnologyIEEE/ACM Transactions on Computational Biology and Bioinformatics
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HPG pore: an efficient and scalable framework for nanopore sequencing data.

2016

The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION™ from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. Here we present HPG Pore, a toolkit for …

0301 basic medicineComputer scienceApplied MathematicsDistributed computingDNASequence Analysis DNAData scienceBiochemistryComputer Science Applications03 medical and health scienceschemistry.chemical_compoundNanoporeNanopores030104 developmental biology0302 clinical medicinechemistryStructural Biology030220 oncology & carcinogenesisScalabilityNanopore sequencingDNA microarrayThroughput (business)Molecular BiologyDNASoftwareBMC bioinformatics
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Deep learning architectures for prediction of nucleosome positioning from sequences data

2018

Abstract Background Nucleosomes are DNA-histone complex, each wrapping about 150 pairs of double-stranded DNA. Their function is fundamental for one of the primary functions of Chromatin i.e. packing the DNA into the nucleus of the Eukaryote cells. Several biological studies have shown that the nucleosome positioning influences the regulation of cell type-specific gene activities. Moreover, computational studies have shown evidence of sequence specificity concerning the DNA fragment wrapped into nucleosomes, clearly underlined by the organization of particular DNA substrings. As the main consequence, the identification of nucleosomes on a genomic scale has been successfully performed by com…

0301 basic medicineComputer scienceCellBiochemistrychemistry.chemical_compound0302 clinical medicineStructural Biologylcsh:QH301-705.5Nucleosome classificationSequenceSettore INF/01 - InformaticabiologyApplied MathematicsEpigeneticComputer Science ApplicationsChromatinNucleosomesmedicine.anatomical_structurelcsh:R858-859.7EukaryoteDNA microarrayDatabases Nucleic AcidComputational biologySaccharomyces cerevisiaelcsh:Computer applications to medicine. Medical informatics03 medical and health sciencesDeep LearningmedicineNucleosomeAnimalsHumansEpigeneticsMolecular BiologyGeneBase Sequencebusiness.industryDeep learningResearchReproducibility of Resultsbiology.organism_classificationYeastNucleosome classification Epigenetic Deep learning networks Recurrent neural networks030104 developmental biologylcsh:Biology (General)chemistryRecurrent neural networksROC CurveDeep learning networksArtificial intelligenceNeural Networks Computerbusiness030217 neurology & neurosurgeryDNABMC Bioinformatics
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Reducing sample size in experiments with animals: historical controls and related strategies

2015

Reducing the number of animal subjects used in biomedical experiments is desirable for ethical and practical reasons. Previous reviews of the benefits of reducing sample sizes have focused on improving experimental designs and methods of statistical analysis, but reducing the size of control groups has been considered rarely. We discuss how the number of current control animals can be reduced, without loss of statistical power, by incorporating information from historical controls, i.e. subjects used as controls in similar previous experiments. Using example data from published reports, we describe how to incorporate information from historical controls under a range of assumptions that mig…

0301 basic medicineComputer scienceDesign of experimentsControl (management)Control subjects01 natural sciencesGeneral Biochemistry Genetics and Molecular BiologyStatistical power010104 statistics & probability03 medical and health sciences030104 developmental biologySample size determinationStatisticsRange (statistics)Statistical analysis0101 mathematicsGeneral Agricultural and Biological SciencesStatistical hypothesis testingBiological Reviews
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A new parallel pipeline for DNA methylation analysis of long reads datasets

2017

Background DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. Results In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while…

0301 basic medicineComputer scienceParallel pipelineADN02 engineering and technologycomputer.software_genreBiochemistrySensitivity and SpecificityDNA sequencingEpigenesis Genetic03 medical and health scienceschemistry.chemical_compoundStructural BiologyRNA analysisInformàticaDatabases Genetic0202 electrical engineering electronic engineering information engineeringHumansEpigeneticsMolecular Biology020203 distributed computingDNA methylationGenome HumanApplied MathematicsParallel pipelineMethylationSequence Analysis DNASupercomputerComputer Science ApplicationsGenòmica030104 developmental biologychemistryGene Expression RegulationDNA methylationMutationData miningHigh performance computingDNA microarraycomputerSequence AlignmentDNASoftware
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2019

As rats learn to search for multiple sources of food or water in a complex environment, they generate increasingly efficient trajectories between reward sites. Such spatial navigation capacity involves the replay of hippocampal place-cells during awake states, generating small sequences of spatially related place-cell activity that we call "snippets". These snippets occur primarily during sharp-wave-ripples (SWRs). Here we focus on the role of such replay events, as the animal is learning a traveling salesperson task (TSP) across multiple trials. We hypothesize that snippet replay generates synthetic data that can substantially expand and restructure the experience available and make learni…

0301 basic medicineComputer sciencePlace cellMachine learningcomputer.software_genreSpatial memorySynthetic data03 medical and health sciencesCellular and Molecular Neuroscience0302 clinical medicineModels of neural computationGeneticsReinforcement learningMolecular BiologyEcology Evolution Behavior and SystematicsEcologybusiness.industryReservoir computingSnippet030104 developmental biologyComputational Theory and MathematicsModeling and SimulationSequence learningArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryPLOS Computational Biology
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Remarks on GRN-type systems

2020

Systems of ordinary differential equations that appear in gene regulatory networks theory are considered. We are focused on asymptotical behavior of solutions. There are stable critical points as well as attractive periodic solutions in two-dimensional and three-dimensional systems. Instead of considering multiple parameters (10 in a two-dimensional system) we focus on typical behaviors of nullclines. Conclusions about possible attractors are made.

0301 basic medicineComputer sciencelcsh:RGeneral EngineeringGene regulatory networkattractorslcsh:MedicineType (model theory)Nullcline03 medical and health sciences030104 developmental biology0302 clinical medicineordinary differential equations030220 oncology & carcinogenesisOrdinary differential equationAttractorgenetic regulatory networksApplied mathematicslcsh:Qlcsh:ScienceFocus (optics)4open
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Dynamic large-scale network synchronization from perception to action

2018

Sensory-guided actions entail the processing of sensory information, generation of perceptual decisions, and the generation of appropriate actions. Neuronal activity underlying these processes is distributed into sensory, fronto-parietal, and motor brain areas, respectively. How the neuronal processing is coordinated across these brain areas to support functions from perception to action remains unknown. We investigated whether phase synchronization in large-scale networks coordinate these processes. We recorded human cortical activity with magnetoencephalography (MEG) during a task in which weak somatosensory stimuli remained unperceived or were perceived. We then assessed dynamic evolutio…

0301 basic medicineComputer sciencemedia_common.quotation_subjectSomatosensorySensory systemSynchronizationSomatosensory systemlcsh:RC321-57103 medical and health sciences0302 clinical medicineArtificial IntelligencePerceptionMotor systemSynchronization (computer science)medicinePremovement neuronal activitylcsh:Neurosciences. Biological psychiatry. Neuropsychiatrymedia_commonMEGmedicine.diagnostic_testApplied MathematicsGeneral NeuroscienceResearchCommunication3112 NeurosciencesMagnetoencephalographyPhase synchronizationComputer Science Applications030104 developmental biologyActionPerceptionNeuroscience030217 neurology & neurosurgery
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Parallel Pairwise Epistasis Detection on Heterogeneous Computing Architectures

2016

This is a post-peer-review, pre-copyedit version of an article published in IEEE Transactions on Parallel and Distributed Systems. The final authenticated version is available online at: http://dx.doi.org/10.1109/TPDS.2015.2460247. [Abstract] Development of new methods to detect pairwise epistasis, such as SNP-SNP interactions, in Genome-Wide Association Studies is an important task in bioinformatics as they can help to explain genetic influences on diseases. As these studies are time consuming operations, some tools exploit the characteristics of different hardware accelerators (such as GPUs and Xeon Phi coprocessors) to reduce the runtime. Nevertheless, all these approaches are not able t…

0301 basic medicineCoprocessorComputer science0206 medical engineeringAccelerationData modelsSymmetric multiprocessor systemComputational modeling02 engineering and technologyParallel computingSupercomputer03 medical and health sciencesTask (computing)030104 developmental biologyCoprocessorsComputational Theory and MathematicsHardware and ArchitectureSignal ProcessingGeneticsPairwise comparisonComputer architectureGraphics processing units020602 bioinformaticsXeon Phi
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Reactome pathway analysis: a high-performance in-memory approach

2016

Reactome aims to provide bioinformatics tools for visualisation, interpretation and analysis of pathway knowledge to support basic research, genome analysis, modelling, systems biology and education. Pathway analysis methods have a broad range of applications in physiological and biomedical research; one of the main problems, from the analysis methods performance point of view, is the constantly increasing size of the data samples. Here, we present a new high-performance in-memory implementation of the well-established over-representation analysis method. To achieve the target, the over-representation analysis method is divided in four different steps and, for each of them, specific data st…

0301 basic medicineData structuresDatabases FactualPathway analysisComputer scienceInterface (Java)Systems biologycomputer.software_genreGenomeBiochemistry03 medical and health sciences0302 clinical medicineStructural BiologyNucleic AcidsHumansMolecular BiologyApplied MathematicsComputational BiologyProteinsPathway analysisComputer Science ApplicationsTree (data structure)030104 developmental biology030220 oncology & carcinogenesisGraph (abstract data type)Data miningOver-representation analysiscomputerAlgorithmsSoftwareBMC Bioinformatics
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