Expectation- maximization algorithm and bayesian methods were used to estimate haplotype frequencies.

An expectation- maximization algorithm is described to account for unknown variance and covariance parameters.

An expectation- maximization algorithm is developed for numerical calculation.

Haplotypes were inferred with an expectation- maximization algorithm, and allelic interaction was analyzed by logistic regression modeling.

We calculated time within primary infection laboratory stages using actual observed transitions and with an expectation- maximization algorithm.

We selected target genes and SNPs primarily using a candidate-SNP approach and estimated haplotypes using the expectation- maximization algorithm.

Here we present an expectation- maximization algorithm built on a pair hidden Markov model that is able to properly handle indels in neutrally evolving DNA sequences.

Haplotypes' frequencies were estimated using the Expectation- Maximization algorithm.