19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Generalized singular value decomposition for comparative analysis of genome-scale expression data sets of two different organisms.

      Proceedings of the National Academy of Sciences of the United States of America

      Cell Cycle, genetics, Data Interpretation, Statistical, Databases, Genetic, Gene Expression Profiling, statistics & numerical data, Genes, Fungal, drug effects, Genomics, Humans, Oligonucleotide Array Sequence Analysis, Pheromones, pharmacology, RNA, Fungal, metabolism, RNA, Messenger, Saccharomyces cerevisiae, cytology, Stress, Physiological

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          We describe a comparative mathematical framework for two genome-scale expression data sets. This framework formulates expression as superposition of the effects of regulatory programs, biological processes, and experimental artifacts common to both data sets, as well as those that are exclusive to one data set or the other, by using generalized singular value decomposition. This framework enables comparative reconstruction and classification of the genes and arrays of both data sets. We illustrate this framework with a comparison of yeast and human cell-cycle expression data sets.

          Related collections

          Author and article information

          Journal
          12631705
          152296
          10.1073/pnas.0530258100

          Comments

          Comment on this article