New algorithms will be developed to handle various analyses of nucleic acid and protein sequences. The algorithms will be designed to take advantage of massively parallel processors for high speed access and computations that will be required for the large amount of information expected to accumulate in the macromolecular sequence databases (especially as the human genome sequencing project gets under way). The algorithms will be used to conduct searching, pattern recognition, and alignments of sequences. They will then be packaged into user-friendly software for DEC and SUN workstations serving as front ends to the parallel processors. In addition, further development of Purdue University's secondary structure program for single-stranded nucleic acids will be undertaken. For this, new algorithms exploiting the simulated annealing approach will be designed to circumvent the problem of local energy minima encountered in this type of analysis.
