Search results for "Regulatory Networks"

showing 10 items of 107 documents

Network reconstruction for trans acting genetic loci using multi-omics data and prior information.

2022

Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…

Data Integrationeducation.field_of_studyComputer scienceScale (chemistry)Bayesian probabilityPopulationQuantitative Trait LociBiological databaseInferenceData Integration ; Machine Learning ; Multi-omics ; Network Inference ; Personalized Medicine ; Prior Information ; Simulation ; Systems BiologyComputational biologyQuantitative trait locusReplication (computing)Machine LearningPrior probabilityCohortGeneticsMolecular MedicineHumans:Medicine [Science]Gene Regulatory NetworkseducationTranscriptomeMolecular BiologyGenetics (clinical)Genome medicine
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Inferring slowly-changing dynamic gene-regulatory networks

2015

Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experi…

Dynamic network analysisL1 penalized inferenceComputer scienceT-LymphocytesGene regulatory networkgene regulatory networkMachine learningcomputer.software_genreBiochemistrygene-regulatory networksStructural Biologygraphical modelscomputer simulationT lymphocyteHumansGene Regulatory NetworkshumanGraphical modelMolecular Biologylymphocyte activationClass (computer programming)Models Statisticalalgorithmbusiness.industryResearchApplied Mathematicsstatistical modelStatistical modelComplex networkQuantitative Biology::GenomicsComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONConditional independencemicroarray analysisComputingMethodologies_GENERALArtificial intelligencebusinessmetabolismRandom variablecomputerAlgorithmsBMC Bioinformatics
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Hub-Centered Gene Network Reconstruction Using Automatic Relevance Determination

2012

Network inference deals with the reconstruction of biological networks from experimental data. A variety of different reverse engineering techniques are available; they differ in the underlying assumptions and mathematical models used. One common problem for all approaches stems from the complexity of the task, due to the combinatorial explosion of different network topologies for increasing network size. To handle this problem, constraints are frequently used, for example on the node degree, number of edges, or constraints on regulation functions between network components. We propose to exploit topological considerations in the inference of gene regulatory networks. Such systems are often…

Dynamic network analysisTranscription GeneticMicroarraysSciencePosterior probabilityGene regulatory networkBiologycomputer.software_genreBioinformaticsNetwork topology03 medical and health sciences0302 clinical medicineYeastsGeneticsComputer SimulationGene Regulatory NetworksGene NetworksBiology030304 developmental biologyRegulatory NetworksHyperparameter0303 health sciencesMultidisciplinaryModels GeneticSystems BiologyQuantitative Biology::Molecular NetworksCell CycleQRComputational BiologyBayesian networkGene Expression RegulationROC CurveMedicineData miningcomputerAlgorithms030217 neurology & neurosurgeryCombinatorial explosionBiological networkResearch ArticlePLoS ONE
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Pathway network inference from gene expression data

2014

[EN] Background: The development of high-throughput omics technologies enabled genome-wide measurements of the activity of cellular elements and provides the analytical resources for the progress of the Systems Biology discipline. Analysis and interpretation of gene expression data has evolved from the gene to the pathway and interaction level, i.e. from the detection of differentially expressed genes, to the establishment of gene interaction networks and the identification of enriched functional categories. Still, the understanding of biological systems requires a further level of analysis that addresses the characterization of the interaction between functional modules. Results: We presen…

ESTADISTICA E INVESTIGACION OPERATIVAGene regulatory networkGene ExpressionInferenceSister chromatidsOxidative Phosphorylation//purl.org/becyt/ford/1 [https]Structural BiologyEstadística e Investigación OperativaGene Regulatory NetworksTopology (chemistry)Alzheimers-DiseaseGeneticsDIBUJOBiological systemsApplied MathematicsSystems BiologyCell Cycle//purl.org/becyt/ford/1.2 [https]Computer Science ApplicationsMicroarray experimentsModeling and SimulationIdentification (biology)Functional assessmentDNA-replicationFunctional connectionsGlycolysisCIENCIAS NATURALES Y EXACTASPathway NetworkDNA ReplicationSaccharomyces-CervisiaeBioinformaticsS-phaseSystems biologyGenomicsComputational biologySaccharomyces cerevisiaeBiologyGene interactionAlzheimer DiseaseModelling and SimulationGenomic dataPANAPathwaysMolecular BiologyUbiquitinResearchGene Expression ProfilingR packageGluconeogenesisGene expression profilingComputingMethodologies_PATTERNRECOGNITIONPurinesCiencias de la Computación e InformaciónProteolysisGene expression dataCiencias de la Información y BioinformáticaUbiquitin conjugationPathwayBMC Systems Biology
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Early asymmetric cues triggering the dorsal/ventral gene regulatory network of the sea urchin embryo

2014

Dorsal/ventral (DV) patterning of the sea urchin embryo relies on a ventrally-localized organizer expressing Nodal, a pivotal regulator of the DV gene regulatory network. However, the inceptive mechanisms imposing the symmetry-breaking are incompletely understood. In Paracentrotus lividus, the Hbox12 homeodomain-containing repressor is expressed by prospective dorsal cells, spatially facing and preceding the onset of nodal transcription. We report that Hbox12 misexpression provokes DV abnormalities, attenuating nodal and nodal-dependent transcription. Reciprocally, impairing hbox12 function disrupts DV polarity by allowing ectopic expression of nodal. Clonal loss-of-function, inflicted by b…

Embryo NonmammalianTranscription GeneticEctodermp38 Mitogen-Activated Protein Kinasessymmetry breakingdorsal ventral axis sea urchin embryo nodal homeodomain repressor p38 MAPKAnimals Genetically ModifiedCell polarityMorphogenesisGene Regulatory NetworksBiology (General)ZebrafishSea urchinsea urchin embryoGeneticsbiologyGeneral NeuroscienceQRdorsal/ventral polarityCell PolarityGene Expression Regulation DevelopmentalEmbryoGeneral MedicineCell biologymedicine.anatomical_structureGene Knockdown Techniquesembryonic structuresParacentrotusMedicineCuesResearch Articleanimal structuresQH301-705.5Nodal ProteinScienceEmbryonic DevelopmentSettore BIO/11 - Biologia Molecolarep38 MAPKModels BiologicalGeneral Biochemistry Genetics and Molecular Biologybiology.animalEctodermmedicineAnimalsBody PatterningHomeodomain ProteinsGeneral Immunology and MicrobiologyotherCell Biologybiology.organism_classificationEmbryonic stem cellhomeodomain repressorRepressor ProteinsDevelopmental Biology and Stem CellsnodalNODALDevelopmental biologyeLife
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Defining the genomic signature of totipotency and pluripotency during early human development.

2013

The genetic mechanisms governing human pre-implantation embryo development and the in vitro counterparts, human embryonic stem cells (hESCs), still remain incomplete. Previous global genome studies demonstrated that totipotent blastomeres from day-3 human embryos and pluripotent inner cell masses (ICMs) from blastocysts, display unique and differing transcriptomes. Nevertheless, comparative gene expression analysis has revealed that no significant differences exist between hESCs derived from blastomeres versus those obtained from ICMs, suggesting that pluripotent hESCs involve a new developmental progression. To understand early human stages evolution, we developed an undifferentiation netw…

EmbryologyBlastomeresMicroarraysCellular differentiationGene ExpressionCell Fate DeterminationMolecular Cell BiologyGene Regulatory NetworksInduced pluripotent stem cellreproductive and urinary physiologyGeneticsMultidisciplinarySystems BiologyStem CellsQTotipotentRGenomic signatureCell DifferentiationGenomicsCell biologyFunctional GenomicsBlastocyst Inner Cell MassBlastocyst Inner Cell Massembryonic structuresMedicineResearch ArticlePluripotent Stem CellsSystems biologyCell PotencyScienceEmbryonic DevelopmentBiologyMolecular GeneticsGeneticsHumansGene NetworksBiologyEmbryonic Stem CellsGenome HumanGene Expression ProfilingBio-OntologiesComputational BiologyMolecular Sequence AnnotationComparative GenomicsMolecular DevelopmentEmbryonic stem cellSignalingSignaling NetworksGene expression profilingGenome Expression AnalysisTotipotent Stem CellsDevelopmental BiologyPLoS ONE
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Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature

2015

Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and d…

EpigenomicsProteomics0301 basic medicineDrugmedia_common.quotation_subjectSystems biologyGene regulatory networkSynthetic lethalityDiseaseComputational biologyBiologyPharmacology03 medical and health sciencesNeoplasmsDrug DiscoveryBiomarkers TumormedicineAnimalsHumansMetabolomicsGene Regulatory NetworksMolecular Targeted TherapyProtein Interaction Mapsmedia_commonPharmacologyPlants MedicinalDrug discoveryGene Expression ProfilingSystems BiologyCancermedicine.diseaseAntineoplastic Agents PhytogenicGene Expression Regulation Neoplastic030104 developmental biologyBiological networkPhytotherapySignal TransductionPharmacological Research
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Gene Regulation and Species-Specific Evolution of Free Flight Odor Tracking in Drosophila

2018

Running title: flight evolution in Drosophila This is an invited contribution to the special issue on Genetics of Adaptation based on a symposium of the same name at the National Centre for Biological Sciences (TIFR, Bangalore, India) in November 2016; International audience; The flying ability of insects has coevolved with the development of organs necessary to take-off from the ground, generate, and modulate lift during flight in complex environments. Flight orientation to the appropriate food source and mating partner depends on the perception and integration of multiple chemical signals. We used a wind tunnel-based assay to investigate the natural and molecular evolution of free flight …

Fatty Acid DesaturasesMale0301 basic medicineFat bodymelanogastercoordinationD. buzzatiiconsequencesReceptors OdorantPheromonesD. suzukiifliesDrosophila ProteinsGene Regulatory Networksfat bodyMatingRegulation of gene expressionbiologysex-pheromonesAnatomyBiological EvolutionoenocytemodulationDrosophilaFemaleFree flightZimbabweGenetic SpeciationsystemD. virilisEvolution Molecular03 medical and health sciencesSex FactorsSpecies Specificitydesaturase geneMolecular evolutiondesat1expressionGeneticsAnimalsMolecular BiologyDrosophilaGeneEcology Evolution Behavior and Systematics[SDV.GEN]Life Sciences [q-bio]/Geneticsfungibiology.organism_classification030104 developmental biologyGene Expression RegulationOdorEvolutionary biologyFlight Animalsexual dimorphismOdorants[ SDV.GEN ] Life Sciences [q-bio]/Genetics
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The peach volatilome modularity is reflected at the genetic and environmental response levels in a QTL mapping population

2014

Background: The improvement of fruit aroma is currently one of the most sought-after objectives in peach breeding programs. To better characterize and assess the genetic potential for increasing aroma quality by breeding, a quantity trait locus (QTL) analysis approach was carried out in an F-1 population segregating largely for fruit traits. Results: Linkage maps were constructed using the IPSC peach 9 K Infinium (R) II array, rendering dense genetic maps, except in the case of certain chromosomes, probably due to identity-by-descent of those chromosomes in the parental genotypes. The variability in compounds associated with aroma was analyzed by a metabolomic approach based on GC-MS to pro…

FitomejoramientoVolatile CompoundsGenotyping TechniquesQuantitative Trait LociPopulationLocus (genetics)Plant ScienceBreedingEnvironmentQuantitative trait locusPolymorphism Single NucleotideCompuesto VolátilPrunusMetabolomicsQTL (Quantitative Trait Loci)Databases GeneticGenotypeCluster AnalysisPrunus PersicaGene Regulatory NetworkseducationAromaAromaLoci de Rasgos CuantitativosGeneticsPrincipal Component AnalysisVolatile Organic Compoundseducation.field_of_studybiologyDuraznoChromosome Mappingfood and beveragesbiology.organism_classificationPlant BreedingFruitPeachesMetabolomeTraitPrunusLod ScoreResearch ArticleBMC Plant Biology
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Dynamics of gene regulatory networks and their dependence on network topology and quantitative parameters – the case of phage λ

2019

Background Gene regulatory networks can be modelled in various ways depending on the level of detail required and biological questions addressed. One of the earliest formalisms used for modeling is a Boolean network, although these models cannot describe most temporal aspects of a biological system. Differential equation models have also been used to model gene regulatory networks, but these frameworks tend to be too detailed for large models and many quantitative parameters might not be deducible in practice. Hybrid models bridge the gap between these two model classes – these are useful when concentration changes are important while the information about precise concentrations and binding…

Gene Expression Regulation ViralHybrid systemsComputer scienceGene regulatory networklcsh:Computer applications to medicine. Medical informaticsNetwork topologyModels BiologicalBiochemistryGene regulatory networks03 medical and health sciences0302 clinical medicineStructural BiologyLysogenic cycleStable behavioursOperonPhage λlcsh:QH301-705.5LysogenyMolecular BiologyTopology (chemistry)030304 developmental biology0303 health sciencesModel validationApplied MathematicsBacteriophage lambdaComputer Science ApplicationsBoolean networkOrder (biology)lcsh:Biology (General)030220 oncology & carcinogenesisHybrid systemMutationlcsh:R858-859.7Biological systemSoftwareResearch ArticleBMC Bioinformatics
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