@article{2047,
  keywords = {Animals, Models, Genetic, Base Sequence, Gene Expression Regulation, Gene Expression Profiling, Gene Regulatory Networks, Green Fluorescent Proteins, Algorithms, Oligonucleotide Array Sequence Analysis, Artificial Intelligence, Data Interpretation, Statistical, Promoter Regions, Genetic, Sequence Homology, Nucleic Acid, Computer Simulation, Reproducibility of Results, Caenorhabditis elegans, MicroRNAs, GATA Transcription Factors},
  author = {Maria Chikina and Curtis Huttenhower and Coleen Murphy and Olga Troyanskaya},
  title = {Global prediction of tissue-specific gene expression and context-dependent gene networks in Caenorhabditis elegans.},
  abstract = {<p>Tissue-specific gene expression plays a fundamental role in metazoan biology and is an important aspect of many complex diseases. Nevertheless, an organism-wide map of tissue-specific expression remains elusive due to difficulty in obtaining these data experimentally. Here, we leveraged existing whole-animal Caenorhabditis elegans microarray data representing diverse conditions and developmental stages to generate accurate predictions of tissue-specific gene expression and experimentally validated these predictions. These patterns of tissue-specific expression are more accurate than existing high-throughput experimental studies for nearly all tissues; they also complement existing experiments by addressing tissue-specific expression present at particular developmental stages and in small tissues. We used these predictions to address several experimentally challenging questions, including the identification of tissue-specific transcriptional motifs and the discovery of potential miRNA regulation specific to particular tissues. We also investigate the role of tissue context in gene function through tissue-specific functional interaction networks. To our knowledge, this is the first study producing high-accuracy predictions of tissue-specific expression and interactions for a metazoan organism based on whole-animal data.</p>},
  year = {2009},
  journal = {PLoS Comput Biol},
  volume = {5},
  pages = {e1000417},
  month = {06/2009},
  language = {eng},
}