N. Chia and R. Bundschuh, Proceedings of the ninth annual international conference on computational molecular biology (RECOMB2005), S. Miyano et al., eds., Springer, (Berlin, Germany, 2005), 474-488 and J. Comp. Biol 13 (2006) 429-441
Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.