A practical approach to significance assessment in alignment with gaps.
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.
Chia
Nicholas
N
Department of Physics, Ohio State University, Columbus, 43210, USA.
Bundschuh
Ralf
R
D000465:Algorithms; D019295:Computational Biology; D016208:Databases, Factual; D016415:Sequence Alignment / Q000706:statistics & numerical data*; D012984:Software