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Fusion methodologies for biomedical data

期刊

JOURNAL OF PROTEOMICS
卷 74, 期 12, 页码 2774-2785

出版社

ELSEVIER
DOI: 10.1016/j.jprot.2011.07.001

关键词

Data integration; Genome-wide data; Transcriptome; Proteome; Bayesian networks; Kernel models

资金

  1. EU DICODE [ICT-2009.4.3, 257184]
  2. EDGE (National Network for Genomic Research) EU
  3. Greek State co-funded Project [09SYN-13-901 EPAN II]

向作者/读者索取更多资源

Data fusion methods are powerful tools for integrating the different views of an organism provided by various types of experimental data. We describe various methodologies for integrating and drawing inferences from a collection of biomedical data, primarily focusing on protein and gene expression data. Computational experiments performed using biomedical data, including known protein-protein interactions, hydropathy profiles, gene expression data and amino acid sequences, demonstrate the utility of this approach. Overall, studies agree in that methodologies using carefully selected data of various types to predict particular classes, groups and interactions, perform better than when applied to a single type of data. (C) 2011 Elsevier B.V. All rights reserved.

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