Search results for "Omics data"

showing 7 items of 7 documents

Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM

2019

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell techno…

0301 basic medicineEpigenomicsMultifactor Dimensionality ReductionComputer scienceGeneral Physics and Astronomy02 engineering and technologyOmics dataMyoblastsMiceSingle-cell analysisGATA1 Transcription FactorMyeloid CellsLymphocyteslcsh:ScienceData processingMultidisciplinaryQGene Expression Regulation DevelopmentalRNA sequencingCell DifferentiationGenomics021001 nanoscience & nanotechnologyData processingDNA-Binding ProteinsInterferon Regulatory FactorsSingle-Cell Analysis0210 nano-technologyAlgorithmsOmics technologiesSignal TransductionLineage differentiationScienceComputational biologyGeneral Biochemistry Genetics and Molecular BiologyArticle03 medical and health sciencesErythroid CellsAnimalsCell LineageGeneral Chemistrydevelopmental trajectories visualizationHematopoietic Stem CellsPipeline (software)Visualization030104 developmental biologyTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESCellular heterogeneitySingle cell analysilcsh:QGene expressionTranscriptomeTranscription FactorsNature Communications
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STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data

2018

AbstractSingle-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.

Omics dataCellular heterogeneityLineage differentiationComputer scienceGenomicsComputational biologyPipeline (software)Visualization
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The role of blood DNA methylation in environment-related chronic disease: a biostatistical toolkit

2013

La epigenética se refiere al estudio de las marcas químicas que alteran la expresión génica sin cambiar la secuencia genética. Los factores ambientales y conductuales son conocidos modificadores de la epigenética, resultando así en cambios heredables que pueden dar lugar a alteraciones en procesos biológicos esenciales y, por consiguiente, al desarrollo de enfermedades. La metilación del ADN es la marca epigenética más estudiada. Existe amplia evidencia científica de la asociación entre factores ambientales tales como tabaco y metales, y desregulaciones en la metilación del ADN. Asimismo, existe amplia evidencia de la asociación entre desregulaciones en metilación del ADN y enfermedades cró…

DNA methylationomics dataUNESCO::CIENCIAS MÉDICAScausal inferencesurvival analysisUNESCO::MATEMÁTICAS
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Direct and Inverse Comorbidities Between Complex Disorders

2016

Comorbidity and multimorbidity, defined as the presence of more than one disease in individuals, have emerged as a major challenge in the last decade (Valderas et al., 2009). Indeed, researchers, health professionals, healthcare managers and policy makers, and patients and citizens are lagging behind considering the comorbidity scenario, as illustrated by the paucity of documentation concerning interventions in people with multiple conditions (Smith et al., 2012). There is a clear need to better understand disease-disease relationships, in order to better organize and provide care, but also to develop appropriate research models. We can first characterize direct multimorbidity (higher-than-…

0301 basic medicineBiopsychosocial modelNosologymedicine.medical_specialtymedicinemultimorbidityPhysiologymalaltiesContext (language use)Disease03 medical and health sciencesPhysiology (medical)MultimorbidityMedicinecomplex diseasesPsychiatryOMICS dataComputingMilieux_MISCELLANEOUSbusiness.industrymedicine.diseaseComorbidity[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]3. Good healthcomorbidityEditorial030104 developmental biologyAge of onsetbusinessNeurocognitive
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Status and prospects of systems biology in grapevine research

2019

The cultivated grapevine, Vitis vinifera L., has gathered a vast amount of omics data throughout the last two decades, driving the imperative use of computational resources for its analysis and integration. Molecular systems biology arises from this need allowing to model and predict the emergence of phenotypes or responses in biological systems. Beyond single omics networks, integrative approaches associate the molecular components of an organism and combine them into higher order networks to model dynamic behaviors. Application of network-based methods in multi-omics data is providing additional resources to address important questions regarding grapevine fruit quality and composition. He…

Settore BIO/11 - BIOLOGIA MOLECOLAREMulti-omicsExploitComputer scienceSystems biologyIntegrative analysisMolecular systemsRegulatory networkData scienceOmics dataMulti omicsGene co-expressionVitis viniferaOrganism
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Integrative bioinformatics and omics data source interoperability in the next-generation sequencing era-Editorial.

2021

With the advent of high-throughput and next-generation sequencing (NGS) technologies [1], huge amounts of ‘omics’ data (i.e. data from genomics, proteomics, pharmacogenomics, metagenomics, etc.) are continuously produced. Combining and integrating diverse omics data types is important in order to investigate the molecular machinery of complex diseases, with the hope for better disease prevention and treatment [2]. Experimental data repositories of omics data are publicly available, with the main aim of fostering the cooperation among research groups and laboratories all over the world. However, despite their openness, the effective integrated use of available public sources is hampered by t…

Omics dataIntegrative bioinformaticsSettore INF/01 - InformaticaComputer scienceInteroperabilityComputational BiologyHigh-Throughput Nucleotide SequencingMolecular BiologyData sciencedata integration omics data sources interoperabilityDNA sequencingInformation SystemsBriefings in bioinformatics
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Integrative Gene Expression and Metabolic Analysis Tool IgemRNA

2022

ABSTRACTGenome scale metabolic modelling is widely used technique to research metabolism impacts on organism’s properties. Additional omics data integration enables a more precise genotype-phenotype analysis for biotechnology, medicine and life sciences. Transcriptome data amounts rapidly increase each year. Many transcriptome analysis tools with integrated genome scale metabolic modelling are proposed. But these tools have own restrictions, compatibility issues and the necessity of previous experience and advanced user skills. We have analysed and classified published tools, summarized possible transcriptome pre-processing, and analysis methods and implemented them in the new transcriptome…

business.industryComputer scienceProcess (engineering)Metabolic networkData validationComputational biologyBiochemistryToolboxTranscriptomeSoftwaregenome-scale metabolic modeling; transcriptomics; software engineering; Cobra Toolbox 3.0; MATLAB; flux balance analysis; flux variability analysis; omics data analysisbusinessFlux (metabolism)Molecular BiologyGraphical user interfaceBiomolecules; Volume 12; Issue 4; Pages: 586
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