Assigning roles to protein mentions: The case of transcription factors
Journal of Biomedical Informatics
EURASIP Journal on Advances in Signal Processing - Special issue on genomic signal processing
Effect of using varying negative examples in transcription factor binding site predictions
EvoBIO'11 Proceedings of the 9th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Improving transcription factor binding site predictions by using randomised negative examples
IPCAT'12 Proceedings of the 9th international conference on Information Processing in Cells and Tissues
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Motivation: Our understanding of gene regulation is currently limited by our ability to collectively synthesize and catalogue transcriptional regulatory elements stored in scientific literature. Over the past decade, this task has become increasingly challenging as the accrual of biologically validated regulatory sequences has accelerated. To meet this challenge, novel community-based approaches to regulatory element annotation are required. Summary: Here, we present the Open Regulatory Annotation (ORegAnno) database as a dynamic collection of literature-curated regulatory regions, transcription factor binding sites and regulatory mutations (polymorphisms and haplotypes). ORegAnno has been designed to manage the submission, indexing and validation of new annotations from users worldwide. Submissions to ORegAnno are immediately cross-referenced to EnsEMBL, dbSNP, Entrez Gene, the NCBI Taxonomy database and PubMed, where appropriate. Availability: ORegAnno is available directly through MySQL, Web services, and online at http://www.oreganno.org. All software is licensed under the Lesser GNU Public License (LGPL). Contact: sjones@bcgsc.ca