Fusion methodologies for biomedical data

被引:10
|
作者
Tsiliki, Georgia [1 ]
Kossida, Sophia [1 ]
机构
[1] Acad Athens, Biomed Res Fdn, Bioinformat & Med Informat Grp, Athens 11527, Greece
关键词
Data integration; Genome-wide data; Transcriptome; Proteome; Bayesian networks; Kernel models; PROTEIN-PROTEIN INTERACTIONS; DATA INTEGRATION METHODOLOGY; GENE-EXPRESSION; FUNCTION PREDICTION; CELLULAR NETWORKS; SYSTEMS BIOLOGY; PROTEOMIC DATA; OMICS DATA; GENOME; TOOL;
D O I
10.1016/j.jprot.2011.07.001
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:2774 / 2785
页数:12
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