Software has become as essential to molecular biologists as the Bunsen burner was a few decades ago. Biological data come mainly in the form of DNA or protein sequences, i.e., strings over alphabets of four or 20 symbols, respectively. The main challenge now is to develop efficient and powerful algorithms to extract as much meaning as possible from the huge amount of data generated in the last few years. In this paper we present a parallel pattern discovery algorithm that given a set of functionally related sequences finds the substrings that occur in all (or most of) the sequences of the set. The occurrences of the substrings can be approximate, that is, can differ up to a maximum number of mismatches that depends on the length of the substrings.
Mauri, G., Pavesi, G. (2002). A parallel algorithm for pattern discovery in biological sequences. FUTURE GENERATION COMPUTER SYSTEMS, 18(6), 849-854 [10.1016/S0167-739X(02)00057-2].
A parallel algorithm for pattern discovery in biological sequences
MAURI, GIANCARLO;
2002
Abstract
Software has become as essential to molecular biologists as the Bunsen burner was a few decades ago. Biological data come mainly in the form of DNA or protein sequences, i.e., strings over alphabets of four or 20 symbols, respectively. The main challenge now is to develop efficient and powerful algorithms to extract as much meaning as possible from the huge amount of data generated in the last few years. In this paper we present a parallel pattern discovery algorithm that given a set of functionally related sequences finds the substrings that occur in all (or most of) the sequences of the set. The occurrences of the substrings can be approximate, that is, can differ up to a maximum number of mismatches that depends on the length of the substrings.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.