Rank discriminants for predicting phenotypes from RNA expression

Preprint, Other literature type English OPEN
Afsari, Bahman; Braga-Neto, Ulisses M.; Geman, Donald;
(2014)

Statistical methods for analyzing large-scale biomolecular data are commonplace in computational biology. A notable example is phenotype prediction from gene expression data, for instance, detecting human cancers, differentiating subtypes and predicting clinical outcome... View more
  • References (69)
    69 references, page 1 of 7

    U. Alon, N. Barkai, D. Notterman, and et al. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. PNAS, 96(12), 1999.

    R. B. Altman, C. A. M. Ho K. Kroemer, and et al. Pharmacogenomics: will the promise be ful lled. Nature Reviews, 12:69{73, 2011.

    T. Anderson, I. Tchernyshyov, R. Diez, and et al. Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data. Proteomics, 7(8), 2007.

    S. Armstrong, J. Staunton, L. Silverman, and et al. Mll translocations specify a distinct gene expression pro le that distinguishes a unique leukemia. Nature Genetics, 30:41{47, 2002.

    C. Au ray. Protein subnetwork markers improve prediction of cancer outcome. Molecular Systems Biology, 3(141), 2007.

    S. Bicciato, M. Pandin, G. Didon, and C. D. Bello. Pattern identi cation and classi cation in gene expression data using an autoassociative neural network model. Biotechnology Bioengineering, 81:594{606, 2003.

    B. Bloated, R. Irizarry, and T. Speed. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics, 19(2):185{193, 2004.

    G. Bloom, I. Yang, D. Boulware, and et al. Multi-platform, multisite, microarray-based human tumor classi cation. American Journal of Pathology, 164:9{16, 2004.

    A. L. Boulesteix, G. Tutz, and K. Strimmer. A cart-based approach to discover emerging patterns in microarray data. Bioinformatics, 19:2465{2472, 2003.

    P. S. Bradley and O. L. Mangasarian. Feature selection via concave minimization and support vector machines. In ICML, pages 82{90, 1998.

  • Related Research Results (1)
  • Related Organizations (2)
  • Metrics
Share - Bookmark