Stable, predictive biomarkers and interpretable disease signatures are seen as a signi cant step towards personalized medicine. In this per- spective, integration of multi-omic data com- ing from genomics, transcriptomics, glycomics, proteomics, metabolomics is a powerful strat- egy to reconstruct and analyse complex mul- ti-dimensional interactions, enabling deeper mechanistic and medical insight. At the same time, there is a rising concern that much of such different omic data -although often publicly and freely available- lie in data- bases and repositories underutilised or not used at all. Issues coming from lack of stand- ardisation and shared biological identities are also well-known. From these considerations, a novel, pressing request arises from the life sciences to design methodologies and approaches that allow for these data to be interpreted as a whole, i.e. as inter- twined molecular signatures containing genes, proteins, mRNAs and miRNAs, able to capture inter-layers connections and complexity. Papers discuss data integration approaches and methods of several types and extents, their application in understanding the pathogenesis of speci c diseases or in identifying candidate biomarkers to exploit the full bene t of multi-omic datasets and their intrinsic information content. Topics of interest include, but are not limited to: o Methods for the integration of layered data, including, but not limited to, genomics, transcrip- tomics, glycomics, proteomics, metabolomics; o Application of multi-omic data integration approaches for diagnostic biomarker discovery in any eld of the life sciences; o Innovative approaches for the analysis and the visualization of multi-omic datasets; o Methods and applications for systematic measurements from single/undivided samples (com- prising genomic, transcriptomic, proteomic, metabolomic measurements, among others); o Multi-scale approaches for integrated dynamic modelling and simulation; o Implementation of applications, computational resources and repositories devoted to data integration including, but not limited to, data warehousing, database federation, semantic integration, service-oriented and/or wiki integration; o Issues related to the de nition and implementation of standards, shared identities and seman- tics, with particular focus on the integration problem.

Multi-omic Data Integration

P Tieri;C Nardini;
2015

Abstract

Stable, predictive biomarkers and interpretable disease signatures are seen as a signi cant step towards personalized medicine. In this per- spective, integration of multi-omic data com- ing from genomics, transcriptomics, glycomics, proteomics, metabolomics is a powerful strat- egy to reconstruct and analyse complex mul- ti-dimensional interactions, enabling deeper mechanistic and medical insight. At the same time, there is a rising concern that much of such different omic data -although often publicly and freely available- lie in data- bases and repositories underutilised or not used at all. Issues coming from lack of stand- ardisation and shared biological identities are also well-known. From these considerations, a novel, pressing request arises from the life sciences to design methodologies and approaches that allow for these data to be interpreted as a whole, i.e. as inter- twined molecular signatures containing genes, proteins, mRNAs and miRNAs, able to capture inter-layers connections and complexity. Papers discuss data integration approaches and methods of several types and extents, their application in understanding the pathogenesis of speci c diseases or in identifying candidate biomarkers to exploit the full bene t of multi-omic datasets and their intrinsic information content. Topics of interest include, but are not limited to: o Methods for the integration of layered data, including, but not limited to, genomics, transcrip- tomics, glycomics, proteomics, metabolomics; o Application of multi-omic data integration approaches for diagnostic biomarker discovery in any eld of the life sciences; o Innovative approaches for the analysis and the visualization of multi-omic datasets; o Methods and applications for systematic measurements from single/undivided samples (com- prising genomic, transcriptomic, proteomic, metabolomic measurements, among others); o Multi-scale approaches for integrated dynamic modelling and simulation; o Implementation of applications, computational resources and repositories devoted to data integration including, but not limited to, data warehousing, database federation, semantic integration, service-oriented and/or wiki integration; o Issues related to the de nition and implementation of standards, shared identities and seman- tics, with particular focus on the integration problem.
2015
Istituto Applicazioni del Calcolo ''Mauro Picone''
978-2-88919-648-7
multi-omics
multi-omic data integration
integration
systems biology
network analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/270474
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