Text-mining assisted regulatory annotation

The Open Regulatory Annotation Consortium,Steven Van Vooren,Steven Jm Jones,Stephen B Montgomery,Obi L Griffith,Casey M Bergman,Stein Aerts,Maximilian Haeussler,Paco Hulpiau

doi:10.1186/gb-2008-9-2-r31

Abstract

Text-mining technologies can be integrated with genome annotation systems, increasing the availability of annotated cis-regulatory data.

Highlights

Decoding transcriptional regulatory networks and the genomic cis-regulatory logic implemented in their control nodes is a fundamental challenge in genome biology
A literature management system for community annotation and text mining Assembling the set of documents that are relevant for annotation and tracking the curatorial status of papers are major challenges in community annotation. To help overcome these issues, we have developed a literature management 'queue' for the ORegAnno database, which allows registered users to input papers with known or suspected cis-regulatory content as targets for curation using their PubMed identifiers (PMIDs)
The ORegAnno Publication Queue was initially populated with expert entries obtained from the set of papers in ORegAnno plus existing sources of curated publications, including the Drosophila DNase I Footprint Database [11], REDfly [12], a catalog of regulatory elements for musclespecific regulation of transcription [13,14], ABS [15], TRED [16], ooTFD [17] and DBTGR [18]

Summary

Introduction

Decoding transcriptional regulatory networks and the genomic cis-regulatory logic implemented in their control nodes is a fundamental challenge in genome biology. Cis-regulatory sequences are typically annotated by manual curation from the literature either under the museum model in the private domain [3] or under a 'boutique' model [4] in the public domain, whereby small teams curate organism- or process-specific datasets from the primary literature for short-term research purposes. Such decentralized resources are disseminated and maintained in ad hoc ways that are often not integrated with the major genome database resources, and can present a bewildering array of choices to the computational or experimental end-user

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