BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

357 related articles for article (PubMed ID: 32592530)

  • 1. A technical review of canonical correlation analysis for neuroscience applications.
    Zhuang X; Yang Z; Cordes D
    Hum Brain Mapp; 2020 Sep; 41(13):3807-3833. PubMed ID: 32592530
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Stability test of canonical correlation analysis for studying brain-behavior relationships: The effects of subject-to-variable ratios and correlation strengths.
    Yang Q; Zhang X; Song Y; Liu F; Qin W; Yu C; Liang M
    Hum Brain Mapp; 2021 Jun; 42(8):2374-2392. PubMed ID: 33624333
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Finding the needle in a high-dimensional haystack: Canonical correlation analysis for neuroscientists.
    Wang HT; Smallwood J; Mourao-Miranda J; Xia CH; Satterthwaite TD; Bassett DS; Bzdok D
    Neuroimage; 2020 Aug; 216():116745. PubMed ID: 32278095
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Permutation inference for canonical correlation analysis.
    Winkler AM; Renaud O; Smith SM; Nichols TE
    Neuroimage; 2020 Oct; 220():117065. PubMed ID: 32603857
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 3D spatially-adaptive canonical correlation analysis: Local and global methods.
    Yang Z; Zhuang X; Sreenivasan K; Mishra V; Curran T; Byrd R; Nandy R; Cordes D
    Neuroimage; 2018 Apr; 169():240-255. PubMed ID: 29248697
    [TBL] [Abstract][Full Text] [Related]  

  • 6. FDR-Corrected Sparse Canonical Correlation Analysis With Applications to Imaging Genomics.
    Gossmann A; Zille P; Calhoun V; Wang YP
    IEEE Trans Med Imaging; 2018 Aug; 37(8):1761-1774. PubMed ID: 29993802
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Canonical Correlation Analysis and Partial Least Squares for Identifying Brain-Behavior Associations: A Tutorial and a Comparative Study.
    Mihalik A; Chapman J; Adams RA; Winter NR; Ferreira FS; Shawe-Taylor J; Mourão-Miranda J;
    Biol Psychiatry Cogn Neurosci Neuroimaging; 2022 Nov; 7(11):1055-1067. PubMed ID: 35952973
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Structured sparse CCA for brain imaging genetics via graph OSCAR.
    Du L; Huang H; Yan J; Kim S; Risacher S; Inlow M; Moore J; Saykin A; Shen L;
    BMC Syst Biol; 2016 Aug; 10 Suppl 3(Suppl 3):68. PubMed ID: 27585988
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A Projection CCA Method for Effective fMRI Data Analysis.
    Qadar MA; Seghouane AK
    IEEE Trans Biomed Eng; 2019 Nov; 66(11):3247-3256. PubMed ID: 30843795
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Tools of the Trade Multivoxel pattern analysis in fMRI: a practical introduction for social and affective neuroscientists.
    Weaverdyck ME; Lieberman MD; Parkinson C
    Soc Cogn Affect Neurosci; 2020 Jun; 15(4):487-509. PubMed ID: 32364607
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.
    Tulay EE; Metin B; Tarhan N; Arıkan MK
    Clin EEG Neurosci; 2019 Jan; 50(1):20-33. PubMed ID: 29925268
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Adding new dimension to neuroscience.
    Holcomb PS
    J Neurosci Res; 2018 Jul; 96(7):1123-1124. PubMed ID: 29570824
    [No Abstract]   [Full Text] [Related]  

  • 13. Enforcing Co-Expression Within a Brain-Imaging Genomics Regression Framework.
    Zille P; Calhoun VD; Wang YP
    IEEE Trans Med Imaging; 2018 Dec; 37(12):2561-2571. PubMed ID: 28678703
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Statistical Learning Methods for Neuroimaging Data Analysis with Applications.
    Zhu H; Li T; Zhao B
    Annu Rev Biomed Data Sci; 2023 Aug; 6():73-104. PubMed ID: 37127052
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Canonical Correlation Analysis With Low-Rank Learning for Image Representation.
    Lu Y; Wang W; Zeng B; Lai Z; Shen L; Li X
    IEEE Trans Image Process; 2022; 31():7048-7062. PubMed ID: 36346858
    [TBL] [Abstract][Full Text] [Related]  

  • 16. On the stability of canonical correlation analysis and partial least squares with application to brain-behavior associations.
    Helmer M; Warrington S; Mohammadi-Nejad AR; Ji JL; Howell A; Rosand B; Anticevic A; Sotiropoulos SN; Murray JD
    Commun Biol; 2024 Feb; 7(1):217. PubMed ID: 38383808
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Group sparse canonical correlation analysis for genomic data integration.
    Lin D; Zhang J; Li J; Calhoun VD; Deng HW; Wang YP
    BMC Bioinformatics; 2013 Aug; 14():245. PubMed ID: 23937249
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of variants of canonical correlation analysis and partial least squares for combined analysis of MRI and genetic data.
    Grellmann C; Bitzer S; Neumann J; Westlye LT; Andreassen OA; Villringer A; Horstmann A
    Neuroimage; 2015 Feb; 107():289-310. PubMed ID: 25527238
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Canonical correlation analysis as a statistical method to relate underwater acoustic propagation and ocean fluctuations.
    L'Her A; Drémeau A; Le Courtois F; Real G; Cristol X; Stéphan Y
    JASA Express Lett; 2022 Oct; 2(10):100801. PubMed ID: 36319215
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A family of locally constrained CCA models for detecting activation patterns in fMRI.
    Zhuang X; Yang Z; Curran T; Byrd R; Nandy R; Cordes D
    Neuroimage; 2017 Apr; 149():63-84. PubMed ID: 28041980
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.