Search results for "Mathematic"

showing 10 items of 24974 documents

Reactome graph database: Efficient access to complex pathway data

2018

Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its qu…

0301 basic medicineDatabases FactualComputer scienceData managementKnowledge BasesSocial SciencesInformation Storage and RetrievalNoSQLcomputer.software_genreComputer ApplicationsDatabase and Informatics MethodsUser-Computer Interface0302 clinical medicineKnowledge extractionPsychologyDatabase Searchinglcsh:QH301-705.5Data ManagementLanguageBiological dataEcologySystems BiologyGenomicsGenomic DatabasesComputational Theory and MathematicsModeling and SimulationWeb-Based ApplicationsGraph (abstract data type)Information TechnologyResearch ArticleComputer and Information SciencesRelational databaseQuery languageResearch and Analysis MethodsEcosystems03 medical and health sciencesCellular and Molecular NeuroscienceDatabasesGeneticsComputer GraphicsHumansMolecular BiologyEcology Evolution Behavior and SystematicsInternetInformation retrievalGraph databasebusiness.industryEcology and Environmental SciencesCognitive PsychologyBiology and Life SciencesComputational BiologyGenome AnalysisRelational Databases030104 developmental biologyBiological Databaseslcsh:Biology (General)Cognitive Sciencebusinesscomputer030217 neurology & neurosurgerySoftwareNeurosciencePLoS Computational Biology
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Longitudinal Investigation into Genetics in the Conservation of Metabolic Phenotypes in Danish and Chinese Twins

2016

Longitudinal twin studies on long term conservation of individual metabolic phenotypes can help to explore the genetic and environmental basis in maintaining metabolic homeostasis and metabolic health. We performed a longitudinal twin study on 12 metabolic phenotypes from Danish twins followed up for 12 years and Chinese twins traced for 7 years. The study covered a relatively large sample of 502 pairs of Danish adult twins with a mean age at intake of 38 years and a total of 181 Chinese adult twin pairs with a mean baseline age of 39.5 years. Bivariate twin models were fitted to the longitudinal measurements taken at two time points (at baseline and follow-up) to estimate the genetic and e…

0301 basic medicineDenmarkTwinslcsh:MedicineGene ExpressionBlood PressureVascular MedicineBiochemistryCorrelation0302 clinical medicineGlucose MetabolismMedicine and Health SciencesEthnicitiesLongitudinal Studieslcsh:Sciencemetabolic phenotypes phenotype stability Danish Chinese twin modelsGeneticsMultidisciplinaryCovarianceDanesPhenotypePhenotypesPhenotypePhysical ScienceslanguageCarbohydrate MetabolismEnvironmental regulationResearch ArticleAdultChina030209 endocrinology & metabolismBivariate analysisBiologyDanish03 medical and health sciencesGeneticsHumansGene RegulationMetabolic healthlcsh:RBiology and Life SciencesRandom VariablesProbability TheoryTwin studylanguage.human_languageMetabolism030104 developmental biologyBlood pressurePeople and Placeslcsh:QPopulation GroupingsMathematicsDevelopmental BiologyPLOS ONE
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On the minimal number of singular fibers with non-compact Jacobians for families of curves over P1

2016

Abstract Let f : X → P 1 be a non-isotrivial family of semi-stable curves of genus g ≥ 1 defined over an algebraically closed field k. Denote by s nc the number of the singular fibers whose Jacobians are non-compact. We prove that s nc ≥ 5 if k = C and g ≥ 5 ; we also prove that s nc ≥ 4 if char ( k ) > 0 and the relative Jacobian of f is non-smooth.

0301 basic medicineDiscrete mathematicsPure mathematicsApplied MathematicsGeneral Mathematics010102 general mathematics01 natural sciences03 medical and health sciencessymbols.namesakeMathematics::Algebraic Geometry030104 developmental biologyGenus (mathematics)Jacobian matrix and determinantFamily of curvessymbols0101 mathematicsAlgebraically closed fieldMathematicsJournal de Mathématiques Pures et Appliquées
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Measuring spectrally-resolved information transfer.

2020

Information transfer, measured by transfer entropy, is a key component of distributed computation. It is therefore important to understand the pattern of information transfer in order to unravel the distributed computational algorithms of a system. Since in many natural systems distributed computation is thought to rely on rhythmic processes a frequency resolved measure of information transfer is highly desirable. Here, we present a novel algorithm, and its efficient implementation, to identify separately frequencies sending and receiving information in a network. Our approach relies on the invertible maximum overlap discrete wavelet transform (MODWT) for the creation of surrogate data in t…

0301 basic medicineDiscrete wavelet transformInformation transferComputer scienceEntropyInformation Theory0302 clinical medicineWaveletMathematical and Statistical TechniquesMedicine and Health SciencesBiology (General)Wavelet TransformsTemporal cortexMammalsEcologySystems BiologyApplied MathematicsSimulation and ModelingPhysicsWavelet transformMagnetoencephalographyEukaryotaBrainSignal FilteringComputational Theory and MathematicsModeling and SimulationPhysical SciencesVertebratesThermodynamicsEngineering and TechnologyWavelet transforms ; Algorithms ; Magnetoencephalography ; Information entropy ; Signal filtering ; Ferrets ; Permutation ; EntropyAnatomyAlgorithmInformation EntropyAlgorithmsResearch ArticleComputer and Information SciencesQH301-705.5PermutationWavelet AnalysisPrefrontal CortexResearch and Analysis Methods03 medical and health sciencesCellular and Molecular NeuroscienceGeneticsEntropy (information theory)AnimalsHumansInformation flow (information theory)Molecular BiologyEcology Evolution Behavior and SystematicsDiscrete MathematicsFerretsOrganismsBiology and Life Sciences030104 developmental biologyCombinatoricsSignal ProcessingAmniotesTransfer entropyZoologyMathematical Functions030217 neurology & neurosurgeryMathematicsPLoS computational biology
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Dynamic coarse-graining fills the gap between atomistic simulations and experimental investigations of mechanical unfolding

2017

We present a dynamic coarse-graining technique that allows to simulate the mechanical unfolding of biomolecules or molecular complexes on experimentally relevant time scales. It is based on Markov state models (MSM), which we construct from molecular dynamics simulations using the pulling coordinate as an order parameter. We obtain a sequence of MSMs as a function of the discretized pulling coordinate, and the pulling process is modeled by switching among the MSMs according to the protocol applied to unfold the complex. This way we cover seven orders of magnitude in pulling speed. In the region of rapid pulling we additionally perform steered molecular dynamics simulations and find excellen…

0301 basic medicineDiscretizationGeneral Physics and AstronomyMarkov processFOS: Physical sciencesCondensed Matter - Soft Condensed Matter01 natural sciences03 medical and health sciencesMolecular dynamicssymbols.namesake0103 physical sciencesPhysics - Biological PhysicsStatistical physicsPhysical and Theoretical Chemistry010306 general physicsPhysicsQuantitative Biology::BiomoleculesMarkov chainMolecular biophysicsBiomolecules (q-bio.BM)Function (mathematics)030104 developmental biologyQuantitative Biology - BiomoleculesOrders of magnitude (time)Biological Physics (physics.bio-ph)FOS: Biological sciencessymbolsSoft Condensed Matter (cond-mat.soft)Granularity
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Attraction in n ‐dimensional differential systems from network regulation theory

2018

0301 basic medicineDynamical systems theoryN dimensionalGeneral MathematicsGeneral Engineering02 engineering and technologyDifferential systemsAttraction03 medical and health sciences020210 optoelectronics & photonics030104 developmental biologyAttractor0202 electrical engineering electronic engineering information engineeringStatistical physicsMathematicsMathematical Methods in the Applied Sciences
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On a Planar Dynamical System Arising in the Network Control Theory

2016

We study the structure of attractors in the two-dimensional dynamical system that appears in the network control theory. We provide description of the attracting set and follow changes this set suffers under the changes of positive parameters µ and Θ.

0301 basic medicineDynamical systems theoryPhase portraitattractor selection020206 networking & telecommunicationsphase portraits02 engineering and technologyDynamical systemnetworks controldynamical systemLinear dynamical system03 medical and health sciences030104 developmental biologyProjected dynamical systemControl theoryModeling and SimulationAttractor0202 electrical engineering electronic engineering information engineeringQA1-939Statistical physicsLimit setRandom dynamical systemAnalysisMathematicsMathematicsMathematical Modelling and Analysis
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Discovering Differential Equations from Earth Observation Data

2020

Modeling and understanding the Earth system is a constant and challenging scientific endeavour. When a clear mechanistic model is unavailable, complex or uncertain, learning from data can be an alternative. While machine learning has provided excellent methods for detection and retrieval, understanding the governing equations of the system from observational data seems an elusive problem. In this paper we introduce sparse regression to uncover a set of governing equations in the form of a system of ordinary differential equations (ODEs). The presented method is used to explicitly describe variable relations by identifying the most expressive and simplest ODEs explaining data to model releva…

0301 basic medicineEarth observationTheoretical computer scienceComputer scienceDifferential equationOde020206 networking & telecommunications02 engineering and technologyData modeling03 medical and health sciences030104 developmental biologyOrdinary differential equation0202 electrical engineering electronic engineering information engineeringConstant (mathematics)Variable (mathematics)IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
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Inferring causation from time series in earth system sciences

2019

The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers.

0301 basic medicineEarth scienceAquatic Ecology and Water Quality ManagementDynamical systems theoryComputer science530 PhysicsDatenmanagement und AnalyseSciencereviewGeneral Physics and Astronomyheart02 engineering and technologyGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesDatabasesLife ScienceCausationStatistical physics thermodynamics and nonlinear dynamicsintermethod comparisonlcsh:Scienceresearch workScientific enterpriseMultidisciplinaryWIMEKSeries (mathematics)QComputational sciencefeasibility study500General ChemistryAquatische Ecologie en Waterkwaliteitsbeheersimulation021001 nanoscience & nanotechnologyData sciencecausal inference climateEarth system scienceEnvironmental sciences030104 developmental biologytime series analysisCausal inferencePerspectiveBenchmark (computing)Observational studylcsh:Qconceptual frameworkdata management0210 nano-technologyClimate sciences
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Strategies for structuring interdisciplinary education in Systems Biology: an European perspective

2016

Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor’s level is traditionally built upon…

0301 basic medicineEngineeringSystems biologymedia_common.quotation_subjectStructuringGeneral Biochemistry Genetics and Molecular BiologyArticleEducation03 medical and health sciences0302 clinical medicineExcellenceMultidisciplinary approachDrug DiscoveryComputingMilieux_COMPUTERSANDEDUCATIONLife ScienceSystems and Synthetic BiologyInnovation/dk/atira/pure/sustainabledevelopmentgoals/industry_innovation_and_infrastructureCurriculummedia_commonVLAGFlexibility (engineering)Systeem en Synthetische BiologieScience & TechnologyManagement sciencebusiness.industry4. EducationApplied MathematicsINF/01 - INFORMATICAGAPGénéralitésSystems Biology Training and education3. Good healthComputer Science Applications030104 developmental biologyAction (philosophy)Modeling and Simulationand InfrastructureSDG 9 - Industry Innovation and InfrastructureMathematical & Computational BiologySystems biologybusinessDisciplineSDG 9 - IndustryLife Sciences & Biomedicine030217 neurology & neurosurgery
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