title: Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms.
abstract: BACKGROUND
  Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes. This approach, which better reflects the functional constraints on the evolution of organisms, can exploit the large amount of data generated by genome-wide expression analyses. However, it requires new methodologies to represent the data in a more accessible way for cross-species comparisons.
  
  
  RESULTS
  In this work, we present an approach based on Multi-dimensional Scaling techniques, to compare the conformation of two gene expression networks, represented in a multi-dimensional space. The expression networks are optimally superimposed, taking into account two criteria: (1) inter-organism orthologous gene pairs have to be nearby points in the final multi-dimensional space and (2) the distortion of the gene expression networks, the organization of which reflects the similarities between the gene expression measurements, has to be circumscribed. Using this approach, we compared the transcriptional programs that drive sporulation in budding and fission yeasts, extracting some common properties and differences between the two species.
authors.affiliation: Laboratoire de Génétique Moléculaire, CNRS UMR 8541, Ecole Normale Supérieure, 46 rue d'Ulm, 75230 Paris cedex 05, France. lelandais@biologie.ens.fr
authors.forename: Gaëlle
authors.initials: G
authors.lastname: Lelandais
authors.forename: Pierre
authors.initials: P
authors.lastname: Vincens
authors.forename: Anne
authors.initials: A
authors.lastname: Badel-Chagnon
authors.forename: Stéphane
authors.initials: S
authors.lastname: Vialette
authors.forename: Claude
authors.initials: C
authors.lastname: Jacq
authors.forename: Serge
authors.initials: S
authors.lastname: Hazout
mesh_terms: D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D005656:Fungal Proteins / Q000737:chemistry; D020869:Gene Expression Profiling / Q000379:methods*; D015966:Gene Expression Regulation, Fungal; D016678:Genome; D015233:Models, Statistical; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D012568:Schizosaccharomyces / Q000378:metabolism; D012984:Software; D013045:Species Specificity
chemical_list: D005656:Fungal Proteins