Computational studies of imprinted genes.
Computational studies on imprinted genes can have very different purposes: one major aim of these studies is the identification of DNA elements that distinguish imprinted genes from biallelically expressed genes. Comparative studies may help to identify imprinting regulatory elements and to understand common mechanisms of imprinted gene regulation in mammalian species. To date, the continuously growing number of genomic and epigenetic data sets makes detailed, genome-wide analyses on imprinted genes feasible. However, imprinted genes are characterized by genomic features that can influence statistics and can make such studies difficult. Hence, comparative computational studies can get very complex and require a tight interaction between bioinformaticians and biologists. Furthermore, analyses of raw data that are generated by micro-array hybridization and high-throughput sequencing technologies require computational approaches that have been designed especially for the epigenetic field. This chapter gives an overview about databases and software that is suitable for analyses of imprinted genes. Furthermore, possible difficulties that are typical for computational and statistical analyses of imprinted genes are described.
Life Sciences, Saarland University, Saarbrücken, Germany. m.paulsen@mx.uni-saarland.de
Martina
M
Paulsen
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D019175:DNA Methylation / Q000235:genetics; D003627:Data Interpretation, Statistical; D057225:Data Mining; D020869:Gene Expression Profiling; D018392:Genomic Imprinting; D023281:Genomics; D006801:Humans; D051379:Mice; D058977:Molecular Sequence Annotation; D012313:RNA / Q000235:genetics
D012313:RNA