title: Maximum-likelihood estimation of the statistical distribution of Smith-Waterman local sequence similarity scores.
abstract: A method is described for estimating the distribution and hence testing the statistical significance of sequence similarity scores obtained during a data-bank search. Maximum-likelihood is used to fit a model to the scores, avoiding any costly simulation of random sequences. The method is applied in detail to the Smith-Waterman algorithm when gaps are allowed, and is shown to give results very similar to those obtained by simulation.
authors: Laboratory of Mathematical Biology, National Institute for Medical Research, Mill Hill, NW7 1AA, London, U.K., r-mott@uk.ac.mrc.nimr.
authors: R
authors: R
authors: Mott
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D016013:Likelihood Functions; D015233:Models, Statistical; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D017385:Sequence Homology; D016008:Statistical Distributions
chemical_list: D011506:Proteins