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WIREs Syst Biol Med
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Integrative biomarker discovery in neurodegenerative diseases

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Data mining has been widely applied in biomarker discovery resulting in significant findings of different clinical and biological biomarkers. With developments in technology, from genomics to proteomics analysis, a deluge of data has become available, as well as standardized data repositories. Nonetheless, researchers are still facing important challenges in analyzing the data, especially when considering the complexity of pathways involved in biological processes and diseases. Data from single sources appear unable to explain complex processes, such as those involved in brain‐related disorders, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis, thus raising the need for a more comprehensive perspective. A possible solution relies on data and model integration, where several data types are combined to provide complementary views. This in turn can result in the discovery of previously unknown biomarkers by unraveling otherwise hidden relationships between data from different sources, and/or validate such composite biomarkers in more powerful predictive models. WIREs Syst Biol Med 2015, 7:357–379. doi: 10.1002/wsbm.1310 This article is categorized under: Analytical and Computational Methods > Computational Methods Translational, Genomic, and Systems Medicine > Translational Medicine
Workflow of a typical integration strategy based on data aggregation at input level. Key: D—data, F—feature, M—model. (Reprinted with permission from Ref . Copyright 2011 Wiley)
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Workflow of a typical integration strategy based on serial integration of data and models. Key: D—data, F—feature, M—model. (Reprinted with permission from Ref . Copyright 2011 Wiley)
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Workflow of a typical integration strategy based on data integration at the model level. We stress that data integration is achieved while building the model, using a kernel function, for example. Key: D—data, F—feature, M—model. (Reprinted with permission from Ref . Copyright 2011 Wiley)
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Workflow of a typical integration strategy based on multiple heterogeneous data and model integration. Key: D—data, F—feature, M—model. (Reprinted with permission from Ref . Copyright 2011 Wiley)
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Translational, Genomic, and Systems Medicine > Translational Medicine
Analytical and Computational Methods > Computational Methods

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