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Finding genes by the positional candidate approach requires abundant cDNAs mapped to chromosomes. To provide such important information, we computationally mapped 19032 of our mouse cDNAs to mouse chromosomes by using data from public databases. We used 2 approaches. In the first, we integrated the mapping data of cDNAs on the human genome, known gene-related data, and comparative mapping data. From this, we calculated map positions on the mouse chromosomes. For this first approach, we developed a simple and powerful criterion to choose the correct map position from candidate positions in sequence homology searches. In the second approach, we related cDNAs to expressed sequence tags (EST) previously mapped in radiation hybrid experiments. We discuss improving the mapping by combining the 2 methods.