W440 Nucleic Acids Research, 2005, Vol. 33, Web Server issue Figure 2. Representation of the comparison of two weight matrices. The upper, yellow one is a probability matrix taken from the example MEME file (Motif 8 in the example file on the help page). The lower, blue one is the Jaspar count matrix MA0028 for Elk-1. The divergence computed by T-Reg Comparator amounts to 0.644. Thin dashed lines indicate the overlapping part. The frames depict the core consensus GGAA of the ETS family of transcription factors. are also highly informative and similar in both matrices. How- ever, the position following GGAA is dissimilar in the two motifs: Motif 8 contains an unambiguous G whereas MA0028 has an A or a G. In summary, Motif 8 is probably a binding site for factors of the ETS family but not necessarily of Elk-1. Indeed, it has been shown previously that another ETS tran- scription factor, GABP, binds some ribosomal proteins’ gene promoters (14). The third PWM in the example ﬁle, Motif 5, shows only poor similarity to other matrices. Hence, this motif can be regarded as novel, at least to the T-Reg database. T-Reg Comparator is a tool designed to support researchers in identifying novel transcription factor binding sites. There are many situations in which researchers come up with weight mat- rices that describe the binding speciﬁcity of a set of transcription factors of interest. Identifying over-represented sequence patterns in sets of regulatory regions in silico (15) or performing in-depth analyses of the binding speciﬁcity of DNA-binding proteins in vitro (16) are just two of many examples. In all these cases, there is a need to check whether some of the sequence patterns match the already described binding speci- ﬁcity of a transcription factor. To this end, the newly identiﬁed PWM must be compared with available data collections such as Transfac and Jaspar. However, these databases do not provide tools or data structures to address this question. In addition, there are further speciﬁc issues that arise when comparing weight matrices. First, PWMs stored in the databases are frequently very short or have many uninformative positions. Second, small PWMs can be parts of larger, modular PWMs (17). And third, single transcription factors can be associated with two or more PWMs, which sometimes differ substantially. T-Reg Comparator is tailored to handle the situation described above. To achieve this, we use a dissimilarity score based on the symmetrized, position-averaged relative entropy, which has already been introduced by De Moor and colleagues for weight matrix comparison (9,10). All pos- sible shifts of the matrices are considered in the comparison, and the one giving the lowest dissimilarity score is reported. In addition, uninformative comparison results are ﬁltered out. We consider a comparison result to be uninformative when only small parts of the matrices have been compared or when the parts compared are highly uninformative. Another important advantage of our method is that we provide a detailed description of the identiﬁed similarities. Reverse-complement or partially overlapping high-scoring matches are readily identiﬁed. Along with the PWMs, we also provide an interface to an elaborate sequence annotation method (11), which is very convenient for many typical ana- lyses of transcription factor binding behaviour. In the future we hope to make this resource the basis for a uniﬁed collection of experimentally and computationally derived PWMs. ACKNOWLEDGEMENTS We thank Stein Aerts for providing us with the names of the PWMs in Transfac Public and Amit Sinha for help with the manuscript. Funding to pay the Open Access publication charges for this article was provided by the Max Planck Institute for Molecular Genetics. 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