Nencki Genomics Database--Ensembl funcgen enhanced with intersections, user data and genome-wide TFBS motifs

Database (Oxford). 2013 Oct 1:2013:bat069. doi: 10.1093/database/bat069. Print 2013.

Abstract

We present the Nencki Genomics Database, which extends the functionality of Ensembl Regulatory Build (funcgen) for the three species: human, mouse and rat. The key enhancements over Ensembl funcgen include the following: (i) a user can add private data, analyze them alongside the public data and manage access rights; (ii) inside the database, we provide efficient procedures for computing intersections between regulatory features and for mapping them to the genes. To Ensembl funcgen-derived data, which include data from ENCODE, we add information on conserved non-coding (putative regulatory) sequences, and on genome-wide occurrence of transcription factor binding site motifs from the current versions of two major motif libraries, namely, Jaspar and Transfac. The intersections and mapping to the genes are pre-computed for the public data, and the result of any procedure run on the data added by the users is stored back into the database, thus incrementally increasing the body of pre-computed data. As the Ensembl funcgen schema for the rat is currently not populated, our database is the first database of regulatory features for this frequently used laboratory animal. The database is accessible without registration using the mysql client: mysql -h database.nencki-genomics.org -u public. Registration is required only to add or access private data. A WSDL webservice provides access to the database from any SOAP client, including the Taverna Workbench with a graphical user interface.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Binding Sites / genetics
  • Databases, Genetic*
  • Genome / genetics*
  • Genomics*
  • Humans
  • Mice
  • Nucleotide Motifs
  • Rats
  • Sequence Alignment
  • Statistics as Topic*
  • Transcription Factors / metabolism*

Substances

  • Transcription Factors