Significados de integrative analysis em inglês

Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data.

We first reconstructed a genome-scale metabolic model and used this for integrative analysis of multilevel omics data.

Method: An integrative analysis was used to study reports, articles, and Website information on the dementia care labour market.

Our integrative analysis using these tools identified numerous mouse genotypes that are likely to have previously uncharacterized autistic-like phenotypes.

Our methodology is based on probabilistic cross-species mapping of functionally analogous proteins based on Bayesian integrative analysis of gene expression compendia.

Genome-scale metabolic models (GEMs) represent extensive knowledgebases that provide a platform for model simulations and integrative analysis of omics data.

Finally, we discuss high-throughput screening strategies that generate multi-parametric datasets that allow integrative analysis of heterogeneous information (imaging and omics approaches).

More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease.

In this study we present the first genome-wide integrative analysis of promoter methylation and gene expression for the identification of methylation markers in melanoma.

These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.

Background: Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems.

Moreover, we highlight the multi-omics integrative analysis as a powerful strategy to efficiently discover and characterize the functional lncRNAs and elucidate their potential molecular mechanisms.

Conclusion: Integrative analysis may uncover informative alterations for an advanced pan-cancer patient population.

Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification.

Integrative analysis of whole-genome and exome sequencing data revealed that COPD and non-COPD groups showed high concordance in mutational burden and spectra.

Methods: We retrieved all reported leprosy-related genes and performed integrative analyses covering gene expression profiling, pathway analysis, protein-protein interaction network, and evolutionary analyses.