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Volumn 32, Issue 18, 2016, Pages 2877-2879

R.JIVE for exploration of multi-source molecular data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; BIOLOGY; HUMAN; INFORMATION PROCESSING; METABOLOMICS; NEOPLASM; PROCEDURES; SOFTWARE;

EID: 84992189556     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btw324     Document Type: Article
Times cited : (61)

References (12)
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  • 4
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    • Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE)
    • Kuligowski, J. et al. (2015) Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE). Analyst, 140, 4521-4529.
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    • Kuligowski, J.1
  • 6
    • 84876058478 scopus 로고    scopus 로고
    • Joint and individual variation explained (JIVE) for integrated analysis of multiple data types
    • Lock, E. et al. (2013) Joint and individual variation explained (JIVE) for integrated analysis of multiple data types. Ann. Appl. Stat., 7, 523-542.
    • (2013) Ann. Appl. Stat. , vol.7 , pp. 523-542
    • Lock, E.1
  • 7
    • 84885617335 scopus 로고    scopus 로고
    • Bayesian consensus clustering
    • Lock, E.F. and Dunson, D.B. (2013) Bayesian consensus clustering. Bioinformatics, 29, 2610-2616.
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    • Lock, E.F.1    Dunson, D.B.2
  • 8
    • 80051934386 scopus 로고    scopus 로고
    • OnPLS - A novel multiblock method for the modelling of predictive and orthogonal variation
    • Löfstedt, T. and Trygg, J. (2011) OnPLS - a novel multiblock method for the modelling of predictive and orthogonal variation. J. Chemom., 25, 441-455.
    • (2011) J. Chemom. , vol.25 , pp. 441-455
    • Löfstedt, T.1    Trygg, J.2
  • 9
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    • Bayesian joint analysis of heterogeneous genomics data
    • Ray, P. et al. (2014) Bayesian joint analysis of heterogeneous genomics data. Bioinformatics, 30, 1370-1376.
    • (2014) Bioinformatics , vol.30 , pp. 1370-1376
    • Ray, P.1
  • 10
    • 84901337323 scopus 로고    scopus 로고
    • Performing disco-sca to search for distinctive and common information in linked data
    • Schouteden, M. et al. (2014) Performing disco-sca to search for distinctive and common information in linked data. Behav. Res. Methods, 46, 576-587.
    • (2014) Behav. Res. Methods , vol.46 , pp. 576-587
    • Schouteden, M.1
  • 11
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    • A non-negative matrix factorization method for detecting modules in heterogeneous omics multi-modal data
    • Yang, Z. and Michailidis, G. (2016) A non-negative matrix factorization method for detecting modules in heterogeneous omics multi-modal data. Bioinformatics, 32, 1-8.
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  • 12
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    • Group component analysis for multiblock data: Common and individual feature extraction
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    • Zhou, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.