OPTIMIZATION OF RIBOSOMAL-RNA PROFILE ALIGNMENTS

Motivation. Large alignments of ribosomal RNA sequences are maintained at various sires. New sequences are added to these alignments using a combination of manual and automatic methods. We examine the use of pr ofile alignment methods for rRNA alignment and try to optimize the cho ice of parameters and sequence weights. Results. Using a large alignme nt of eukaryotic SSU rRNA sequences as a test case, we empirically com pared the performance of various sequence weighting schemes over a ran ge of gap penalties. We developed a new weighting scheme which gives m ost weight to the sequences in the profile that are most similar to th e new sequence. We show that it gives the most accurate alignments whe n combined with a more traditional sequence weighting scheme.