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Modeling Transcription Factor Target Promoters 135Fig. 1. TFBS prediction by PWM approach: a schematic representation of positionfrequency matrix (PFM) and PWM construction. The PWM is used to scan the promotersequences to score the TFBSs. Experimentally known EREs from Jin et al. (24) wereused to prepare the PFM. PFM is converted to PWM, which is in log scale for efficientcomputational analysis.in orthologous human and mouse promoter sequences. Systematic analyses ofsequence conservation in known human TFBSs was performed to demonstratethe use of sequence conservation as a useful criterion to identify putative bindingsites (55,56). Several phylogenetic footprinting methods have been developed foridentifying putative binding sites for TFs with known PWMs.Alignment-based methods, such as rVISTA (57) and ConSite (58), firstcompute a multiple sequence alignment of the set of orthologous sequencesand then scan for TFBSs in the conserved regions using PWMs. If the regulatoryregions are too divergent and fail to align properly, de novo programs,such as FootPrinter (42,59), can be used to identify sets of subsequences thatexhibit a high degree of conservation given a set of orthologous inputsequences and the phylogenetic tree relating them. Blanco et al. (60) proposeda new approach in which they first translate the nucleotide sequenceof the promoter into an alphabet of different symbols representing differentTFs of known PWMs. These TF-maps of two related promoters (e.g., oforthologous or coexpressed genes) were then aligned using global pair-wisealignment method. In this protocol, the use of alignment-based methods or