D66 Nucleic Acids Research, 2006, Vol. 34, Database issue the TSS, as expected. The TFs that appear more frequently are TBP (14.6% of sites), SP1 (13.6%) and CEBP (5.6%). Those TFs are known to be part of the core of many eukaryotic promoters (see the ABS documentation for further details about the contents of the database). WEB INTERFACE Data retrieval The ABS database can be accessed through a simple CGI/ Perl-based web interface at http://genome.imim.es/datasets/ abs2005/index.html. On-line documentation and tutorials are provided for each web service. The following functionalities are implemented in the current release (see Figure 1): (i) For each gene in the collection, show the orthologous promoters and a list of experimentally verified TFBSs annotated on the corresponding sequence. Promoter sequence alignments, computational predictions, dotplots and cross-references to other well-known databases, such as GenBank, Entrez Gene and PubMed, are also provided for each annotation. (ii) Retrieve all of the binding motifs associated with a given TF, filtering by species. Moreover, a global alignment of the motifs is provided and the corresponding sequence logo representation is displayed by using WebLogo (17). This information could be used to produce new profiles for subsequent detection of this TF in other promoters. (iii) Retrieve all of the promoter sequences in which at least one binding site for a given TF was annotated. These sequences and the associated motifs could be used to gen- erate datasets based on known sites to train motif-finding programs. (iv) The gene catalogue, the promoter sequences, the collection of annotations, the sequence alignments and the com- putational predictions are also individually distributed in several flat files. Benchmarking and evaluation tools The ABS database aims to become a platform to evaluate new algorithms for the discovery of novel regulatory elements in a set of related gene promoters (e.g. orthologous promoters or co-regulated genes from microarray experiments). In addition to the data retrieval functions, two on-line applications are available to perform the benchmarking of such algorithms (see Figure 2): (i) Constructor is a web server to produce synthetic datasets based on the ABS annotations. The design of the benchmark is highly flexible allowing to customize the number of sequences, their length, the background nucleotide distri- bution, the number of motifs to plant on them, the prob- ability to plant a motif, the species and the TFs for which the associated motifs will be randomly selected from the known sites collection. The output consists of the artificial sequences with the embedded motifs, the list of motifs and a graphical representation of the occurrences in the sequences produced with the program gff2ps (18). (ii) Evaluator is a web server to determine the accuracy of a set of predicted motifs in several sequences using a list of known binding sites as a reference set. Both sets must be provided by the user in GFF format. A complete accuracy assessment at both nucleotide and site levels is computed using the standard measures in the field (7,19). CONCLUSIONS AND FUTURE WORK The ABS database has been developed to ﬁll the existing gap in the availability of consistent datasets to train and com- pare different pattern discovery programs. The lack of stan- dard collections of TFBSs is specially serious in the case of phylogenetic footprinting data. The collection described here contains 650 experimental TFBSs identiﬁed in human, mouse, rat and chicken genes. Orthologous promoter sequences and their binding sites have been manually curated from biblio- graphy. Supplementary information about the promoters is also provided for each entry. In addition, two web applications (Constructor and Evaluator) are included in this ﬁrst release to facilitate the development of new motif-ﬁnding programs using the ABS annotations. In the next release, we plan to increase the number of annotations adding known sites in regulatory regions different from the proximal promoter and eventually incorporate binding motifs from other species. ACKNOWLEDGEMENTS E.B. is recipient of a predoctoral fellowship from Ministerio de Ciencia y Tecnolog´ıa (Spain). D.F. is recipient of a predoc- toral fellowship from Instituto Nacional de Bioinforma´tica (Spain). This work has been supported by grants from Plan Nacional de I+D (BIO2000-1358-C02-02 and BIO2002- 04426-C02-01), Ministerio de Ciencia y Tecnolog´ıa (Spain) and from a FBBVA Bioinformatics grant. 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