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showing 10 items of 14511 documents

L1-Penalized Censored Gaussian Graphical Model

2018

Graphical lasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. Typical examples are data generated by polymerase chain reactions and flow cytometer. The combination of censoring and high-dimensionality make inference of the underlying genetic networks from these data very challenging. In this article, we propose an $\ell_1$-penalized Gaussian graphical model for censored data and derive two EM-like algorithm…

0301 basic medicineStatistics and ProbabilityFOS: Computer and information sciencesgraphical lassoComputer scienceGaussianNormal DistributionInferenceMultivariate normal distribution01 natural sciencesMethodology (stat.ME)010104 statistics & probability03 medical and health sciencessymbols.namesakeGraphical LassoExpectation–maximization algorithmHumansComputer SimulationGene Regulatory NetworksGraphical model0101 mathematicsStatistics - MethodologyEstimation theoryReverse Transcriptase Polymerase Chain ReactionEstimatorexpectation-maximization algorithmGeneral MedicineCensoring (statistics)High-dimensional datahigh-dimensional dataGaussian graphical model030104 developmental biologysymbolscensored dataCensored dataExpectation-Maximization algorithmStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaAlgorithmAlgorithms
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Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks.

2016

Abstract Factorial Gaussian graphical Models (fGGMs) have recently been proposed for inferring dynamic gene regulatory networks from genomic high-throughput data. In the search for true regulatory relationships amongst the vast space of possible networks, these models allow the imposition of certain restrictions on the dynamic nature of these relationships, such as Markov dependencies of low order – some entries of the precision matrix are a priori zeros – or equal dependency strengths across time lags – some entries of the precision matrix are assumed to be equal. The precision matrix is then estimated by l 1-penalized maximum likelihood, imposing a further constraint on the absolute value…

0301 basic medicineStatistics and ProbabilityFactorialDependency (UML)Computer scienceGaussianNormal Distributionpenalized inferencesparse networkscomputer.software_genreMachine learning01 natural sciencesNormal distribution010104 statistics & probability03 medical and health sciencessymbols.namesakeSparse networksGeneticsComputer SimulationGene Regulatory NetworksGraphical model0101 mathematicsgene-regulatory systemMolecular BiologyProbabilityMarkov chainModels GeneticPenalized inferencebusiness.industryModel selectiongraphical modelGene-regulatory systemsComputational Mathematics030104 developmental biologysymbolsA priori and a posterioriData miningArtificial intelligenceGraphical modelsSettore SECS-S/01 - StatisticabusinesscomputerNeisseriaAlgorithmsStatistical applications in genetics and molecular biology
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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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Sustained oscillations in the MAP kinase cascade.

2016

Abstract The MAP kinase cascade is a network of enzymatic reactions arranged in layers. In each layer occurs a multiple futile cycle of phosphorylations. The fully phosphorylated substrate then serves as an enzyme for the layer below. This paper focuses on the existence of parameters for which Hopf bifurcations occur and generate periodic orbits. Furthermore it is explained how geometric singular perturbation theory allows to generalize results from simple models to more complex ones.

0301 basic medicineStatistics and ProbabilitySingular perturbationDynamical systems theoryMolecular Networks (q-bio.MN)Dynamical Systems (math.DS)MAP kinase cascadeGeneral Biochemistry Genetics and Molecular BiologyQuantitative Biology::Subcellular Processes03 medical and health sciencessymbols.namesakeSimple (abstract algebra)Classical Analysis and ODEs (math.CA)FOS: MathematicsQuantitative Biology - Molecular NetworksSustained oscillationsMathematics - Dynamical SystemsHopf bifurcationPhysics030102 biochemistry & molecular biologyGeneral Immunology and MicrobiologyFutile cycleApplied MathematicsQuantitative Biology::Molecular NetworksGeneral Medicine030104 developmental biologyClassical mechanicsMathematics - Classical Analysis and ODEsModeling and SimulationFOS: Biological sciencessymbolsPeriodic orbitsGeneral Agricultural and Biological SciencesMathematical biosciences
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On the origin of mitosing cells: A historical appraisal of Lynn Margulis endosymbiotic theory

2017

Although for a long-time symbiosis was considered to be quite rare and with no role in evolutionary processes, Lynn Margulis demonstrated that endosymbiotic events played a key role in the origin and evolution of eukaryotic cells. Starting with her seminal assay in the Journal of Theoretical Biology in 1967 (authored as Lynn Sagan), her lifelong work on eukaryogenesis and the role of symbiosis in evolution stands as a valid and authoritative contribution to science. As was quick to acknowledge, she was not the first to discuss the significance of symbiosis to explain the origin of mitochondria and chloroplasts, but no one else had done it to her extent and depth, nor had anyone provided a v…

0301 basic medicineStatistics and ProbabilitySymbiogenesisChloroplastsBiologyGenomeGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciences0302 clinical medicineSymbiosisSymbiosisGeneticsGenomeGeneral Immunology and MicrobiologyApplied MathematicsEukaryotaGeneral MedicineBiological evolutionHistory 20th CenturyBiological EvolutionMitochondria030104 developmental biologyEvolutionary biologyModeling and SimulationGeneral Agricultural and Biological SciencesMetabolic Networks and Pathways030217 neurology & neurosurgeryJournal of Theoretical Biology
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A Systematic Study of Dysregulated MicroRNA in Type 2 Diabetes Mellitus

2017

MicroRNAs (miRNAs) are small noncoding RNAs that modulate the cellular transcriptome at the post-transcriptional level. miRNA plays important roles in different disease manifestation, including type 2 diabetes mellitus (T2DM). Many studies have characterized the changes of miRNAs in T2DM, a complex systematic disease; however, few studies have integrated these findings and explored the functional effects of the dysregulated miRNAs identified. To investigate the involvement of miRNAs in T2DM, we obtained and analyzed all relevant studies published prior to 18 October 2016 from various literature databases. From 59 independent studies that met the inclusion criteria, we identified 158 dysregu…

0301 basic medicineSystematic surveytype 2 diabetes mellitussystematic study030209 endocrinology & metabolismDiseaseBioinformaticsCatalysisArticleInorganic ChemistryTranscriptomelcsh:Chemistry03 medical and health sciences0302 clinical medicineDiabetes mellitusmiRNA-mRNA interaction networkmicroRNAmedicineHumansGene Regulatory NetworksRNA MessengerPhysical and Theoretical Chemistry10. No inequalityMolecular Biologylcsh:QH301-705.5SpectroscopyAdipocytokine Signaling PathwaymicroRNA; type 2 diabetes mellitus; miRNA-mRNA interaction network; systematic studymicroRNAbusiness.industryGene Expression ProfilingOrganic ChemistryType 2 Diabetes MellitusGeneral Medicinemedicine.diseaseComputer Science ApplicationsMicroRNAs030104 developmental biologyDiabetes Mellitus Type 2Gene Expression Regulationlcsh:Biology (General)lcsh:QD1-999Organ SpecificityRNA InterferenceDisease manifestationbusinessTranscriptomeSignal TransductionInternational Journal of Molecular Sciences
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Primary Sensorimotor Cortex Drives the Common Cortical Network for Gamma Synchronization in Voluntary Hand Movements

2018

Background: Gamma synchronization (GS) may promote the processing between functionally related cortico-subcortical neural populations. Our aim was to identify the sources of GS and to analyze the direction of information flow in cerebral networks at the beginning of phasic movements, and during medium-strength isometric contraction of the hand. Methods: We measured 64-channel electroencephalography in 11 healthy volunteers (age: 25 ± 8 years; four females); surface electromyography detected the movements of the dominant hand. In Task 1, subjects kept a constant medium-strength contraction of the first dorsal interosseus muscle, and performed a superimposed repetitive voluntary self-paced br…

0301 basic medicineThalamusPosterior parietal cortexIsometric exerciseElectromyographyElectroencephalographylcsh:RC321-57103 medical and health sciencesBehavioral Neuroscience0302 clinical medicinedirectionalitymedicinelcsh:Neurosciences. Biological psychiatry. NeuropsychiatryBiological PsychiatryOriginal ResearchPhysicsgamma synchronizationmedicine.diagnostic_testhand movementsSMA*Dorsolateral prefrontal cortexPsychiatry and Mental health030104 developmental biologyNeuropsychology and Physiological Psychologymedicine.anatomical_structureNeurologyconnectivitynetworkNeuroscience030217 neurology & neurosurgeryNeuroscienceMotor cortexFrontiers in Human Neuroscience
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Identification of control targets in Boolean molecular network models via computational algebra

2015

Motivation: Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The pot…

0301 basic medicineTheoretical computer scienceComputer scienceProcess (engineering)Molecular Networks (q-bio.MN)Systems biologySystem of polynomial equationsENCODEBoolean networksSet (abstract data type)03 medical and health sciences0302 clinical medicineStructural BiologyModelling and SimulationQuantitative Biology - Molecular NetworksMolecular BiologyEdge deletionsApplied MathematicsComputer Science ApplicationsNetwork controlIdentification (information)030104 developmental biologyBoolean networkBlocking transitionsFOS: Biological sciencesModeling and SimulationAlgebraic controlState (computer science)030217 neurology & neurosurgeryResearch ArticleBMC Systems Biology
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Accelerating metagenomic read classification on CUDA-enabled GPUs.

2016

Metagenomic sequencing studies are becoming increasingly popular with prominent examples including the sequencing of human microbiomes and diverse environments. A fundamental computational problem in this context is read classification; i.e. the assignment of each read to a taxonomic label. Due to the large number of reads produced by modern high-throughput sequencing technologies and the rapidly increasing number of available reference genomes software tools for fast and accurate metagenomic read classification are urgently needed. We present cuCLARK, a read-level classifier for CUDA-enabled GPUs, based on the fast and accurate classification of metagenomic sequences using reduced k-mers (…

0301 basic medicineTheoretical computer scienceWorkstationGPUsComputer scienceContext (language use)CUDAParallel computingBiochemistryGenomelaw.invention03 medical and health sciencesCUDAUser-Computer Interface0302 clinical medicineStructural BiologylawTaxonomic assignmentHumansMicrobiomeMolecular BiologyInternetXeonApplied MathematicsHigh-Throughput Nucleotide SequencingSequence Analysis DNAExact k-mer matchingComputer Science Applications030104 developmental biologyTitan (supercomputer)Metagenomics030220 oncology & carcinogenesisMetagenomicsDNA microarraySoftwareBMC bioinformatics
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