title: Ortho2ExpressMatrix--a web server that interprets cross-species gene expression data by gene family information.
abstract: BACKGROUND
  The study of gene families is pivotal for the understanding of gene evolution across different organisms and such phylogenetic background is often used to infer biochemical functions of genes. Modern high-throughput experiments offer the possibility to analyze the entire transcriptome of an organism; however, it is often difficult to deduct functional information from that data.
  
  
  RESULTS
  To improve functional interpretation of gene expression we introduce Ortho2ExpressMatrix, a novel tool that integrates complex gene family information, computed from sequence similarity, with comparative gene expression profiles of two pre-selected biological objects: gene families are displayed with two-dimensional matrices. Parameters of the tool are object type (two organisms, two individuals, two tissues, etc.), type of computational gene family inference, experimental meta-data, microarray platform, gene annotation level and genome build. Family information in Ortho2ExpressMatrix bases on computationally different protein family approaches such as EnsemblCompara, InParanoid, SYSTERS and Ensembl Family. Currently, respective all-against-all associations are available for five species: human, mouse, worm, fruit fly and yeast. Additionally, microRNA expression can be examined with respect to miRBase or TargetScan families. The visualization, which is typical for Ortho2ExpressMatrix, is performed as matrix view that displays functional traits of genes (differential expression) as well as sequence similarity of protein family members (BLAST e-values) in colour codes. Such translations are intended to facilitate the user's perception of the research object.
  
  
  CONCLUSIONS
  Ortho2ExpressMatrix integrates gene family information with genome-wide expression data in order to enhance functional interpretation of high-throughput analyses on diseases, environmental factors, or genetic modification or compound treatment experiments. The tool explores differential gene expression in the light of orthology, paralogy and structure of gene families up to the point of ambiguity analyses. Results can be used for filtering and prioritization in functional genomic, biomedical and systems biology applications. The web server is freely accessible at http://bioinf-data.charite.de/o2em/cgi-bin/o2em.pl.
authors.affiliation: Structural Bioinformatics Group, Institute for Physiology, Charité-University Medicine Berlin, Thielallee 71, 14195 Berlin, Germany. thomas.meinel@charite.de
authors.forename: Thomas
authors.initials: T
authors.lastname: Meinel
authors.forename: Michal R
authors.initials: MR
authors.lastname: Schweiger
authors.forename: Andreas H
authors.initials: AH
authors.lastname: Ludewig
authors.forename: Ramu
authors.initials: R
authors.lastname: Chenna
authors.forename: Sylvia
authors.initials: S
authors.lastname: Krobitsch
authors.forename: Ralf
authors.initials: R
authors.lastname: Herwig
mesh_terms: D000818:Animals; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D020407:Internet; D051379:Mice; D012984:Software