K. Suzuki (suzuken@kuicr.kyoto-u.ac.jp)
Y. Akiyama (akiyama@kuicr.kyoto-u.ac.jp)
M. Kanehisa (kanehisa@kuicr.kyoto-u.ac.jp)
Institute for Chemical Research, Kyoto University
Gokasho, Uji, Kyoto 611 Japan
We have developed a novel method for multiple sequence alignment based on combinatorial selection of similar block candidates. Our method resembles manual multiple alignment performed by biologists. The method is more feasible for finding functional motifs than previous multiple alignment algorithms that are extensions of pairwise alignments. We employed a Hopfield neural network technique so that the method can cope with the combinatorial explosion in examining a large number of "incomplete" block candidates.