Figure 1. Generation of data of the miRNAMap resource. database, 62, 34 and 4% were present in the intergenic, intronic and exonic regions, respectively. DATA GENERATION Figure 1 presents a ﬂow chart of the generation of data of the miRNAMap database. It comprises the following three main steps: (i) integration of the known miRNA precursors and the miRNA targets; (ii) identiﬁcation of the miRNA precursors and the mature miRNAs and (iii) prediction of the miRNA targets. Each step is described in detail later. Integration of known miRNA precursors and miRNA targets The experimentally validated miRNA genes in the four mam- malian genomes—human, mouse, rat and dog—are obtained from the miRBase (release 6.0) (3). Table 1 indicates that 707 miRNAs were extracted from the miRBase. Only 29 experimentally validated miRNA targets, including the miRNAs and their target genes, are taken from the literature (Table S3). Prediction of miRNA precursors and mature miRNAs The known miRNA genes were obtained from miRBase (3), and putative miRNA precursors were identiﬁed by RNAz (4), along with the four genomes. RNAz is a computational tool for predicting non-coding RNA structures based on comparative sequence analysis. All of the annotated coding exons were removed from the conserved regions obtained from the UCSC Genome Browser (9). A total of 438 788 alignments of the non-coding regions that are conserved in the four mammals—human, mouse, rat and dog—were retained. This number represents 82.64 MBase or 2.88% of the Nucleic Acids Research, 2006, Vol. 34, Database issue D137 human genome. Then, RNAz was used to detect the non- coding RNA structures against the sequences of the conserved regions above. The following constraints were imposed to ﬁlter the non-coding RNA structures of the putative miRNA precursors; (i) the height of the stem of the non- coding RNA structure exceeds 20 nt; (ii) the RNAz z-score of the structure is less than 3.5. Hence, 2681, 2231, 1751 and 2233 putative miRNA precursors were present in human, mouse, rat and dog, respectively. After the putative miRNA precursors had been identiﬁed, the mature miRNA of the putative miRNA genes were identiﬁed. Therefore, a machine learning method was pro- posed to determine computationally the mature miRNA in the miRNA precursors. Figure S3 presents the proposed algo- rithm (Supplementary Data). The detail of the process under- gone by the mature miRNA detector is described in the Supplementary Data. In humans, mice, rats and dogs, 464, 395, 274 and 336 putative miRNAs, respectively, are found to contain the putative mature miRNAs. A comparison of sequences of the miRNA precursors demonstrates that 153 of the putative human miRNA precursors are found to be highly homologous to the known miRNA obtained from the miRBase (3). Prediction of miRNA targets miRanda (1) was incorporated into the proposed miRNAMap to identify the miRNA targets, which were the most probable miRNA targets of the miRNAs against the conserved regions in 30-UTR of the genes of the four genomes and thus predict the target genes of the known miRNAs and the putative miRNAs. The conserved regions in 30-UTR of the genes are derived from the UCSC conserved regions, which are at least 200 bp long and have sequence identities >60% (9); each transcript is effectively annotated in the Ensembl database (10). From human, mouse, rat and dog genomes, 8360, 6923, 1857 and 19 707 30-UTR conserved regions are extracted, respectively. Reference is made to the literature that records the known miRNA targets (Table S3). The predictive parameters including miRanda MFE and miRanda score are adjusted for the miRNA target prediction by comparing the predictive results with known miRNA/ targets data. It resulted that 27 known miRNA/targets among 29 known miRNA/targets were successfully identiﬁed (Table S3). The MFE threshold of the miRNA and target duplex was speciﬁed as 12 kcal/mol and the miRanda score was speciﬁed as 120. Therefore, the miRNA targets whose MFEs are < 12 kcal/mol and the score exceeds 120 are identiﬁed and compiled in the miRNAMap database. The relationships between the miRNAs and the target genes are determined with reference to the genomic locations and the annotations of the coding genes. The miRNAMap also yields expression proﬁles of the known miRNAs, cross-species com- parisons, gene annotations and various cross-links to other biological databases. The annotations of the coding genes were obtained from the Ensembl database (10), Gene Ontol- ogy (11) and HGNC gene grouping/family data (12). The conserved regions among the four selected genomes in the database are obtained from the UCSC Genome Browser (9). The reader should refer to Table S1 in the Supplementary Data for the integrated databases.