Methods for the integration of multi-omics data: mathematical aspects

Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number o...
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Autor*in:	Bersanelli, Matteo [verfasserIn] Mosca, Ettore Remondini, Daniel Giampieri, Enrico Sala, Claudia Castellani, Gastone Milanesi, Luciano

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Omics Multi-omics Data integration

Anmerkung:	© Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd.

Übergeordnetes Werk:	Enthalten in: BMC bioinformatics - London : BioMed Central, 2000, 17(2016), Suppl 2 vom: 20. Jan.
Übergeordnetes Werk:	volume:17 ; year:2016 ; number:Suppl 2 ; day:20 ; month:01

Links:	Volltext

DOI / URN:	10.1186/s12859-015-0857-9

Katalog-ID:	SPR026908212

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allfields	10.1186/s12859-015-0857-9 doi (DE-627)SPR026908212 (SPR)s12859-015-0857-9-e DE-627 ger DE-627 rakwb eng Bersanelli, Matteo verfasserin aut Methods for the integration of multi-omics data: mathematical aspects 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd. Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. Omics (dpeaa)DE-He213 Multi-omics (dpeaa)DE-He213 Data integration (dpeaa)DE-He213 Mosca, Ettore aut Remondini, Daniel aut Giampieri, Enrico aut Sala, Claudia aut Castellani, Gastone aut Milanesi, Luciano aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 17(2016), Suppl 2 vom: 20. Jan. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:17 year:2016 number:Suppl 2 day:20 month:01 https://dx.doi.org/10.1186/s12859-015-0857-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 Suppl 2 20 01
spelling	10.1186/s12859-015-0857-9 doi (DE-627)SPR026908212 (SPR)s12859-015-0857-9-e DE-627 ger DE-627 rakwb eng Bersanelli, Matteo verfasserin aut Methods for the integration of multi-omics data: mathematical aspects 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd. Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. Omics (dpeaa)DE-He213 Multi-omics (dpeaa)DE-He213 Data integration (dpeaa)DE-He213 Mosca, Ettore aut Remondini, Daniel aut Giampieri, Enrico aut Sala, Claudia aut Castellani, Gastone aut Milanesi, Luciano aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 17(2016), Suppl 2 vom: 20. Jan. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:17 year:2016 number:Suppl 2 day:20 month:01 https://dx.doi.org/10.1186/s12859-015-0857-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 Suppl 2 20 01
allfields_unstemmed	10.1186/s12859-015-0857-9 doi (DE-627)SPR026908212 (SPR)s12859-015-0857-9-e DE-627 ger DE-627 rakwb eng Bersanelli, Matteo verfasserin aut Methods for the integration of multi-omics data: mathematical aspects 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd. Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. Omics (dpeaa)DE-He213 Multi-omics (dpeaa)DE-He213 Data integration (dpeaa)DE-He213 Mosca, Ettore aut Remondini, Daniel aut Giampieri, Enrico aut Sala, Claudia aut Castellani, Gastone aut Milanesi, Luciano aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 17(2016), Suppl 2 vom: 20. Jan. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:17 year:2016 number:Suppl 2 day:20 month:01 https://dx.doi.org/10.1186/s12859-015-0857-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 Suppl 2 20 01
allfieldsGer	10.1186/s12859-015-0857-9 doi (DE-627)SPR026908212 (SPR)s12859-015-0857-9-e DE-627 ger DE-627 rakwb eng Bersanelli, Matteo verfasserin aut Methods for the integration of multi-omics data: mathematical aspects 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd. Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. Omics (dpeaa)DE-He213 Multi-omics (dpeaa)DE-He213 Data integration (dpeaa)DE-He213 Mosca, Ettore aut Remondini, Daniel aut Giampieri, Enrico aut Sala, Claudia aut Castellani, Gastone aut Milanesi, Luciano aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 17(2016), Suppl 2 vom: 20. Jan. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:17 year:2016 number:Suppl 2 day:20 month:01 https://dx.doi.org/10.1186/s12859-015-0857-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 Suppl 2 20 01
allfieldsSound	10.1186/s12859-015-0857-9 doi (DE-627)SPR026908212 (SPR)s12859-015-0857-9-e DE-627 ger DE-627 rakwb eng Bersanelli, Matteo verfasserin aut Methods for the integration of multi-omics data: mathematical aspects 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd. Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. Omics (dpeaa)DE-He213 Multi-omics (dpeaa)DE-He213 Data integration (dpeaa)DE-He213 Mosca, Ettore aut Remondini, Daniel aut Giampieri, Enrico aut Sala, Claudia aut Castellani, Gastone aut Milanesi, Luciano aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 17(2016), Suppl 2 vom: 20. Jan. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:17 year:2016 number:Suppl 2 day:20 month:01 https://dx.doi.org/10.1186/s12859-015-0857-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 Suppl 2 20 01
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source	Enthalten in BMC bioinformatics 17(2016), Suppl 2 vom: 20. Jan. volume:17 year:2016 number:Suppl 2 day:20 month:01
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title_sort	methods for the integration of multi-omics data: mathematical aspects
title_auth	Methods for the integration of multi-omics data: mathematical aspects
abstract	Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd.
abstractGer	Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd.
abstract_unstemmed	Background Methods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem. Results and Conclusions We review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects. © Bersanelli et al. 2016. This article is published under license to BioMed Central Ltd.
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title_short	Methods for the integration of multi-omics data: mathematical aspects
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Methods for the integration of multi-omics data: mathematical aspects

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