Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes.
Pubmed ID: 16420670 RIS Download
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WormBook is a comprehensive, open-access collection of original, peer-reviewed chapters covering topics related to the biology of Caenorhabditis elegans and other nematodes. Wormbook also contains WormMethods, a collection of protocols for nematode researchers, and the Worm Breeder''s Gazette, an informal, non-refereed, biannual newsletter for the interchange of ideas and information related to C. elegans and other nematodes. WormBook is the online text companion to WormBase, the C. elegans model organism database. WormBook contains original reviews on all aspects of C. elegans biology and up-to-date descriptions of technical procedures used to study this animal. WormBook Sections: *Genetics and genomics *Molecular biology *Biochemistry *Cell biology *Developmental control *Post-embryonic development *Sex determination *The germ line *Signal transduction *Neurobiology and behavior *Evolution and ecology *Disease models and drug discovery
View all literature mentionsService providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.
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