![]() ![]() ![]() Unlike specialized programs, a general alignment algorithm can be applied to find homologs of any query sequence(s). In primary sequence analysis, the most useful analysis techniques are general primary sequence alignment algorithms with probabilistically based scoring systems – for example, the BLAST, FASTA, or CLUSTALW algorithms, and the PAM or BLOSUM score matrices. All of these approaches, though powerful, lack generality, and they require expert knowledge about each particular RNA family of interest. In several cases, specialized programs have been developed to recognize specific RNA structures – for example, programs exist for detecting transfer RNA genes, group I catalytic introns, and small nucleolar RNAs. Exact- and approximate-match pattern searches (analogous to PROSITE patterns for proteins) have been extended to allow patterns to specify long-range base pairing constraints. Some excellent approaches have been developed for database searching with RNA secondary structure consensus patterns. Computational analyses of RNA sequence families are more powerful if they take into account both primary sequence and secondary structure consensus. Many (though not all) RNAs conserve a base-paired RNA secondary structure. There are a growing number of RNA gene families and RNA motifs.
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