Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer

Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer

Background: Cancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific (“individual”) patterns of variability. At the same time, statistical associations and potent...

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Bibliographic Details
Main Authors: Haugdahl Nøst, T. (Author), Møllersen, K. (Author), Ponzi, E. (Author), Thoresen, M. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Alkylation
Association reactions
Biological organs
Biological process
Blood
Breast Neoplasms
breast tumor
case control study
Case-Control Studies
Clinical outcome
cohort analysis
Cohort Studies
Data integration
Dimension reduction
Diseases
female
Female
Forecasting
genomics
Genomics
human
Humans
Individual components
Integration techniques
Integrative analysis
Joint and individual variance explained
microRNA
MicroRNAs
Multi-omics
Prediction model
Prediction models
Predictive analytics
Predictive models
Quality control
Quality of predictions
Regression analysis
RNA
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Internet

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