The comparative analysis of statistics, based on the likelihood ratio criterion, in the automated annotation problem.
BACKGROUND
This paper discusses the problem of automated annotation. It is a continuation of the previous work on the A4-algorithm (Adaptive algorithm of automated annotation) developed by Leontovich and others.


RESULTS
A number of new statistics for the automated annotation of biological sequences is introduced. All these statistics are based on the likelihood ratio criterion.


CONCLUSIONS
Some of the statistics yield a prediction quality that is significantly higher (up to 1.5 times higher) in comparison with the results obtained with the A4-procedure.
Leontovich
Andrey M
AM
Belozersky Institute of Physico-Chemical Biology, Moscow State University, Moscow 119899, Russia. aml@genebee.msu.su
Tokmachev
Konstantin Y
KY
van Houwelingen
Hans C
HC
D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D016013:Likelihood Functions; D008957:Models, Genetic; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D017421:Sequence Analysis / Q000379:methods*