title: Fusion methodologies for biomedical data.
abstract: 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.
authors.affiliation: Bioinformatics andMedical Informatics Group, Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 115 27, Athens, Greece. gtsiliki@bioacademy.gr
authors.forename: Georgia
authors.initials: G
authors.lastname: Tsiliki
authors.forename: Sophia
authors.initials: S
authors.lastname: Kossida
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D005786:Gene Expression Regulation; D006801:Humans; D008954:Models, Biological; D014176:Protein Biosynthesis; D011506:Proteins / Q000737:chemistry / Q000235:genetics
chemical_list: D011506:Proteins