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Items: 1 to 20 of 125

1.

MOGSA: Integrative Single Sample Gene-set Analysis of Multiple Omics Data.

Meng C, Basunia A, Peters B, Gholami AM, Kuster B, Culhane AC.

Mol Cell Proteomics. 2019 Aug 9;18(8 suppl 1):S153-S168. doi: 10.1074/mcp.TIR118.001251. Epub 2019 Jun 26.

2.

A multivariate approach to the integration of multi-omics datasets.

Meng C, Kuster B, Culhane AC, Gholami AM.

BMC Bioinformatics. 2014 May 29;15:162. doi: 10.1186/1471-2105-15-162.

3.

Translational Metabolomics of Head Injury: Exploring Dysfunctional Cerebral Metabolism with Ex Vivo NMR Spectroscopy-Based Metabolite Quantification.

Wolahan SM, Hirt D, Glenn TC.

In: Kobeissy FH, editor. Brain Neurotrauma: Molecular, Neuropsychological, and Rehabilitation Aspects. Boca Raton (FL): CRC Press/Taylor & Francis; 2015. Chapter 25.

4.

Graph Algorithms for Condensing and Consolidating Gene Set Analysis Results.

Savage SR, Shi Z, Liao Y, Zhang B.

Mol Cell Proteomics. 2019 Aug 9;18(8 suppl 1):S141-S152. doi: 10.1074/mcp.TIR118.001263. Epub 2019 May 29.

5.

Confero: an integrated contrast data and gene set platform for computational analysis and biological interpretation of omics data.

Hermida L, Poussin C, Stadler MB, Gubian S, Sewer A, Gaidatzis D, Hotz HR, Martin F, Belcastro V, Cano S, Peitsch MC, Hoeng J.

BMC Genomics. 2013 Jul 29;14:514. doi: 10.1186/1471-2164-14-514.

6.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

Meng C, Culhane A.

Methods Mol Biol. 2016;1418:19-38. doi: 10.1007/978-1-4939-3578-9_2.

PMID:
27008008
7.

mixOmics: An R package for 'omics feature selection and multiple data integration.

Rohart F, Gautier B, Singh A, Lê Cao KA.

PLoS Comput Biol. 2017 Nov 3;13(11):e1005752. doi: 10.1371/journal.pcbi.1005752. eCollection 2017 Nov.

8.

Topological integration of RPPA proteomic data with multi-omics data for survival prediction in breast cancer via pathway activity inference.

Kim TR, Jeong HH, Sohn KA.

BMC Med Genomics. 2019 Jul 11;12(Suppl 5):94. doi: 10.1186/s12920-019-0511-x.

9.

Massive integrative gene set analysis enables functional characterization of breast cancer subtypes.

Rodriguez JC, Merino GA, Llera AS, Fernández EA.

J Biomed Inform. 2019 May;93:103157. doi: 10.1016/j.jbi.2019.103157. Epub 2019 Mar 27.

PMID:
30928514
10.

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

Kaever A, Landesfeind M, Feussner K, Morgenstern B, Feussner I, Meinicke P.

PLoS One. 2014 Feb 28;9(2):e89297. doi: 10.1371/journal.pone.0089297. eCollection 2014.

11.

Predicting censored survival data based on the interactions between meta-dimensional omics data in breast cancer.

Kim D, Li R, Dudek SM, Ritchie MD.

J Biomed Inform. 2015 Aug;56:220-8. doi: 10.1016/j.jbi.2015.05.019. Epub 2015 Jun 3.

12.

Single sample scoring of molecular phenotypes.

Foroutan M, Bhuva DD, Lyu R, Horan K, Cursons J, Davis MJ.

BMC Bioinformatics. 2018 Nov 6;19(1):404. doi: 10.1186/s12859-018-2435-4.

13.

A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data.

Mo Q, Shen R, Guo C, Vannucci M, Chan KS, Hilsenbeck SG.

Biostatistics. 2018 Jan 1;19(1):71-86. doi: 10.1093/biostatistics/kxx017.

14.

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses.

Nakayasu ES, Nicora CD, Sims AC, Burnum-Johnson KE, Kim YM, Kyle JE, Matzke MM, Shukla AK, Chu RK, Schepmoes AA, Jacobs JM, Baric RS, Webb-Robertson BJ, Smith RD, Metz TO.

mSystems. 2016 May 10;1(3). pii: e00043-16. eCollection 2016 May-Jun.

15.

GSAR: Bioconductor package for Gene Set analysis in R.

Rahmatallah Y, Zybailov B, Emmert-Streib F, Glazko G.

BMC Bioinformatics. 2017 Jan 24;18(1):61. doi: 10.1186/s12859-017-1482-6.

16.

CARMO: a comprehensive annotation platform for functional exploration of rice multi-omics data.

Wang J, Qi M, Liu J, Zhang Y.

Plant J. 2015 Jul;83(2):359-74. doi: 10.1111/tpj.12894.

17.

Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes.

Kim S, Herazo-Maya JD, Kang DD, Juan-Guardela BM, Tedrow J, Martinez FJ, Sciurba FC, Tseng GC, Kaminski N.

BMC Genomics. 2015 Nov 11;16:924. doi: 10.1186/s12864-015-2170-4.

18.

Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.

Argelaguet R, Velten B, Arnol D, Dietrich S, Zenz T, Marioni JC, Buettner F, Huber W, Stegle O.

Mol Syst Biol. 2018 Jun 20;14(6):e8124. doi: 10.15252/msb.20178124.

19.

BRCA-Pathway: a structural integration and visualization system of TCGA breast cancer data on KEGG pathways.

Kim I, Choi S, Kim S.

BMC Bioinformatics. 2018 Feb 19;19(Suppl 1):42. doi: 10.1186/s12859-018-2016-6.

20.

A probabilistic multi-omics data matching method for detecting sample errors in integrative analysis.

Lee E, Yoo S, Wang W, Tu Z, Zhu J.

Gigascience. 2019 Jul 1;8(7). pii: giz080. doi: 10.1093/gigascience/giz080.

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