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showing 10 items of 7541 documents

Evaluation of the Possibility to Detect Circulating Tumor DNA From Pituitary Adenoma

2019

Objective: Circulating free DNA (cfDNA) in general and circulating tumor DNA (ctDNA) in particular is becoming an increasingly used form of liquid biopsy biomarkers. In this study, we are investigating the ability to detect ctDNA from the plasma of pituitary adenoma (PA) patients. Design: Tumor tissue samples were obtained from planed PA resections, before which blood plasma samples were taken. Somatic variants found in PA tissue samples were evaluated in related cfDNA, isolated from plasma samples. Methods: Sanger sequencing, as well as previously obtained whole-exome sequencing data, were used to evaluate somatic variants composition in tumor tissue samples. cfDNA was isolated from the sa…

0301 basic medicineSomatic cellEndocrinology Diabetes and Metabolism030209 endocrinology & metabolismpituitary adenomaBiologylcsh:Diseases of the endocrine glands. Clinical endocrinologyDNA sequencing03 medical and health sciencessymbols.namesakeGNAS0302 clinical medicineEndocrinologyBlood plasmaTaqManGNAS complex locusLiquid biopsyOriginal ResearchSanger sequencingcirculating tumor DNAlcsh:RC648-665AmpliconMolecular biology030104 developmental biologybiology.proteinsymbolsnext-generation sequencingcompetitive allele-specific TaqManFrontiers in Endocrinology
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Partitioned learning of deep Boltzmann machines for SNP data.

2016

Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…

0301 basic medicineStatistics and ProbabilityComputer scienceMachine learningcomputer.software_genre01 natural sciencesBiochemistryPolymorphism Single NucleotideMachine Learning010104 statistics & probability03 medical and health sciencessymbols.namesakeJoint probability distributionHumans0101 mathematicsMolecular BiologyStatistical hypothesis testingArtificial neural networkbusiness.industryGene Expression Regulation LeukemicDeep learningUnivariateComputational BiologyManifoldComputer Science ApplicationsData setComputational Mathematics030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONComputational Theory and MathematicsLeukemia MyeloidBoltzmann constantsymbolsData miningArtificial intelligencebusinesscomputerSoftwareCurse of dimensionalityBioinformatics (Oxford, England)
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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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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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Biomolecular computers with multiple restriction enzymes

2017

Abstract The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton t…

0301 basic medicineTheoretical computer scienceDNA computerlcsh:QH426-4700102 computer and information sciencesBiology01 natural scienceslaw.inventionrestriction enzymesGenomics and Bioinformatics03 medical and health sciencessymbols.namesakeSoftwareDNA computinglawGeneticsNondeterministic finite automatonMolecular BiologyQuantum computerFinite-state machinebusiness.industryConstruct (python library)bioinformaticsDNARestriction enzymelcsh:Genetics030104 developmental biology010201 computation theory & mathematicssymbolsbusinessVon Neumann architectureGenetics and Molecular Biology
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Next‐generation sequencing reveals the mutational landscape of clinically diagnosed Usher syndrome: copy number variations, phenocopies, a predominan…

2017

Background Combined retinal degeneration and sensorineural hearing impairment is mostly due to autosomal recessive Usher syndrome (USH1: congenital deafness, early retinitis pigmentosa (RP); USH2: progressive hearing impairment, RP). Methods Sanger sequencing and NGS of 112 genes (Usher syndrome, nonsyndromic deafness, overlapping conditions), MLPA, and array-CGH were conducted in 138 patients clinically diagnosed with Usher syndrome. Results A molecular diagnosis was achieved in 97% of both USH1 and USH2 patients, with biallelic mutations in 97% (USH1) and 90% (USH2), respectively. Quantitative readout reliably detected CNVs (confirmed by MLPA or array-CGH), qualifying targeted NGS as one …

0301 basic medicineUsher syndromeNonsense mutationnext‐generation sequencingBiologyGene mutationBioinformatics03 medical and health sciencessymbols.namesakeRetinitis pigmentosaGeneticsmedicineotorhinolaryngologic diseasesMultiplex ligation-dependent probe amplificationNonsyndromic deafnessMolecular BiologyGenetics (clinical)Sanger sequencingGeneticsHeimler syndromeCopy number variationPoint mutationOriginal Articlesmedicine.diseaseeye diseases030104 developmental biologysymbolsphenocopiestranslational read‐throughOriginal ArticleUsher syndromeMolecular Genetics & Genomic Medicine
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Actin Filaments Are Involved in the Coupling of V0-V1 Domains of Vacuolar H+-ATPase at the Golgi Complex*

2016

We previously reported that actin-depolymerizing agents promote the alkalization of the Golgi stack and the trans-Golgi network. The main determinant of acidic pH at the Golgi is the vacuolar-type H+-translocating ATPase (V-ATPase), whose V1 domain subunits B and C bind actin. We have generated a GFP-tagged subunit B2 construct (GFP-B2) that is incorporated into the V1 domain, which in turn is coupled to the V0 sector. GFP-B2 subunit is enriched at distal Golgi compartments in HeLa cells. Subcellular fractionation, immunoprecipitation, and inversal FRAP experiments show that the actin depolymerization promotes the dissociation of V1-V0 domains, which entails subunit B2 translocation from Go…

0301 basic medicineVacuolar Proton-Translocating ATPasesGolgi ApparatusBiologyMicrofilamentBiochemistry03 medical and health sciencessymbols.namesakeCytosolHumansActin-binding proteinMolecular BiologyLipid raftActinGolgi membraneCell BiologyIntracellular MembranesGolgi apparatusHydrogen-Ion ConcentrationActin cytoskeletonCell biologyProtein Structure TertiaryCytosolActin Cytoskeleton030104 developmental biologysymbolsbiology.proteinHeLa Cells
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2019

Golgi α-mannosidase II (GMII) is a glycoside hydrolase playing a crucial role in the N-glycosylation pathway. In various tumour cell lines, the distribution of N-linked sugars on the cell surface is modified and correlates with the progression of tumour metastasis. GMII therefore is a possible molecular target for anticancer agents. Here, we describe the identification of a non-competitive GMII inhibitor using computer-aided drug design methods including identification of a possible allosteric binding site, pharmacophore search and virtual screening.

0301 basic medicineVirtual screeningMultidisciplinaryChemistryCellAllosteric regulationGolgi apparatus010402 general chemistry01 natural sciencesEnzyme structure0104 chemical sciences03 medical and health sciencessymbols.namesake030104 developmental biologymedicine.anatomical_structureBiochemistrymedicinesymbolsGlycoside hydrolaseBinding sitePharmacophorePLOS ONE
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Fractional hereditariness of lipid membranes: Instabilities and linearized evolution

2016

In this work lipid ordering phase changes arising in planar membrane bilayers is investigated both accounting for elas- ticity alone and for effective viscoelastic response of such assemblies. The mechanical response of such membranes is studied by minimizing the Gibbs free energy which penalizes perturbations of the changes of areal stretch and their gradients only [1]. As material instabilities arise whenever areal stretches characterizing homogeneous configurations lie inside the spinoidal zone of the free energy density, bifurcations from such configurations are shown to occur as oscillatory perturbations of the in-plane displacement. Experimental observations [2] show a power-law in-pl…

0301 basic medicineViscoelastic lipid membranePhase transitionMembrane Fluidity0206 medical engineeringLipid BilayersBiomedical EngineeringSeparation of variablesFOS: Physical sciences02 engineering and technologyviscoelastic lipid membranesCondensed Matter - Soft Condensed Matterfractional hereditary lipid membranesViscoelasticityFractional hereditary lipid membraneMaterial instabilitieBiomaterials03 medical and health sciencessymbols.namesakeFractional hereditary lipid membranes; Material instabilities; Phase transitions; Viscoelastic lipid membranes; Biomaterials; Biomedical Engineering; Mechanics of MaterialsVariational principleElasticity (economics)Phase transitionMembranesChemistryOscillationTime evolutionBiomaterial020601 biomedical engineeringElasticityGibbs free energyphase transitions030104 developmental biologyClassical mechanicsModels ChemicalMechanics of MaterialssymbolsSoft Condensed Matter (cond-mat.soft)material instabilitiesSettore ICAR/08 - Scienza Delle Costruzionifractional hereditary lipid membranes viscoelastic lipid membranes phase transitions material instabilities
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