Nucleic Acids Research, 2006, Vol. 34, Database issue D63–D67 doi:10.1093/nar/gkj116 ABS: a database of Annotated regulatory Binding Sites from orthologous promoters Enrique Blanco1,2,*, Dome` nec Farre´ 1,2, M. Mar Alba` 1, Xavier Messeguer2 and Roderic Guigo´ 1 1Grup de Recerca en Informa` tica Biome` dica, Institut Municipal d’Investigacio´ Me` dica/Universitat Pompeu Fabra/Centre de Regulacio´ Geno` mica, C/Doctor Aiguader 80, 08003 Barcelona, Spain and 2Grup d’algor´ısmica i gene` tica, Departament de Llenguatges i Sistemes Informa` tics, Universitat Polite` cnica de Catalunya, C/Jordi Girona 1-3, 08034 Barcelona, Spain Received August 1, 2005; Revised September 19, 2005; Accepted October 18, 2005 ABSTRACT Information about the genomic coordinates and the sequence of experimentally identified transcrip- tion factor binding sites is found scattered under a variety of diverse formats. The availability of standard collections of such high-quality data is important to design, evaluate and improve novel computational approaches to identify binding motifs on promoter sequences from related genes. ABS (http://genome. imim.es/datasets/abs2005/index.html) is a public database of known binding sites identified in promot- ers of orthologous vertebrate genes that have been manually curated from bibliography. We have anno- tated 650 experimental binding sites from 68 tran- scription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. A simple and easy-to-use web interface facilitates data retrieval allowing different views of the information. In addi- tion, the release 1.0 of ABS includes a customizable generator of artificial datasets based on the known sites contained in the collection and an evaluation tool to aid during the training and the assessment of motif-finding programs. INTRODUCTION Expression of genes is regulated at many different levels, transcription of DNA being one of the most critical stages. Speciﬁc conﬁgurations of transcription factors (TFs) that inter- act with gene promoter regions are recruited to activate or modulate the production of a given transcript. Many of these TFs possess the ability to recognize a small set of genomic sequence footprints called TF-binding sites (TFBSs). These motifs are typically 6–15 bp long and in some cases, they show a high degree of variability. In addition, many motifs may ambiguously be recognized by members of different TF fami- lies. Because of these ﬂexible binding rules, computational methods for the identiﬁcation of regulatory elements in a promoter sequence tend to produce an overwhelming amount of false positives. However, the identiﬁcation of conserved regulatory elements present in orthologous gene promoters (also called phylogenetic footprinting) has proved to be more effective to characterize such sequences (1–3). In fact, the ever-growing availability of more genomes and the con- stant improvement of bioinformatics algorithms hold great promise for unveiling the overall network of gene interactions of each organism (4). Typically, computational methods to detect regulatory elements use their own training set of experimental annotated TFBSs. These annotations are usually collected from biblio- graphy or from general repositories of gene regulation information, such as JASPAR (5) and TRANSFAC (6). How- ever, each program establishes different criteria and formats to retrieve and display the data that forms the ﬁnal training set, which makes the comparison between different methods very difﬁcult. The construction of a good benchmark to evaluate the accuracy of several pattern discovery methods is therefore not a trivial procedure (7). Although important efforts are being carried out to stan- dardize the construction of collections of promoter regions (8) or the presentation of experimental data (9), there is a clear necessity to provide stable and common datasets for future algorithmic developments. In this direction, we present here the release 1.0 of the ABS database constructed from literature annotations that have been experimentally veriﬁed in human, mouse, rat or chicken. DATABASE CONSTRUCTION We have gathered from the literature a collection of experi- mentally validated binding sites that are conserved in at least *To whom correspondence should be addressed. Tel: +34 93 2240891; Fax: +34 93 2240875; Email: eblanco@imim.es The Author 2006. Published by Oxford University Press. All rights reserved. The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org