title: GOSim--an R-package for computation of information theoretic GO similarities between terms and gene products.
abstract: BACKGROUND
  With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the analysis of such data often there is the need to further explore the similarity of genes not only with respect to their expression, but also with respect to their functional annotation which can be obtained from Gene Ontology (GO).
  
  
  RESULTS
  We present the freely available software package GOSim, which allows to calculate the functional similarity of genes based on various information theoretic similarity concepts for GO terms. GOSim extends existing tools by providing additional lately developed functional similarity measures for genes. These can e.g. be used to cluster genes according to their biological function. Vice versa, they can also be used to evaluate the homogeneity of a given grouping of genes with respect to their GO annotation. GOSim hence provides the researcher with a flexible and powerful tool to combine knowledge stored in GO with experimental data. It can be seen as complementary to other tools that, for instance, search for significantly overrepresented GO terms within a given group of genes.
  
  
  CONCLUSIONS
  GOSim is implemented as a package for the statistical computing environment R and is distributed under GPL within the CRAN project.
authors.affiliation: German Cancer Research Center (DKFZ), Div. Molecular Genome Analysis, Im Neuenheimer Feld 580, Heidelberg, Germany. h.froehlich@dkfz.de
authors.forename: Holger
authors.initials: H
authors.lastname: Fröhlich
authors.forename: Nora
authors.initials: N
authors.lastname: Speer
authors.forename: Annemarie
authors.initials: A
authors.lastname: Poustka
authors.forename: Tim
authors.initials: T
authors.lastname: Beissbarth
mesh_terms: D001483:Base Sequence; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D016247:Information Storage and Retrieval / Q000379:methods; D008969:Molecular Sequence Data; D011381:Programming Languages; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software