Steinar Thorvaldsen | Search PubMed

PubMed2006

Markov model of haploid random mating with given distribution of population size.

An exact Markov chain model is formulated and computed for random mating in a haploid gamete pool. There are two versions of the gamete, and there is a finite number of diploid monoecious organisms. The founder population is given, and the subsequent generations allow a prescribed statistical distribution over different population sizes. The non-homogeneous Markov chain works on the haploid gamete level provided the probability of self-fertilization is 1/n, where n is the number of diploid individuals. Standard deviations of gamete frequencies and fixation probabilities are calculated. Effective population sizes for different population size distributions are estimated, including periodic bottlenecks.

Genetics, Population↗

PubMed2005

A tutorial on Markov models based on Mendel's classical experiments.

Hidden Markov Models (HMM) can be extremely useful tools for the analysis of data from biological sequences, and provide a probabilistic model of protein families. Most reviews and general introductions follow the excellent tutorial by Rabiner, where the focus is outside biology. Mendel's famous experiments in plant hybridisation were published in 1866 and are often considered the icebreaking work of modern genetics. He had no prior knowledge of the dual nature of genes, but through a series of experiments he was able to anticipate the hidden concept and name it "Elemente". In this paper we present the background, theory and algorithms of HMM based on examples from Mendel's experiments, and introduce the toolbox "mendelHMM". This approach is considered to have some intuitive advantages in a biological and bioinformatical setting. Applications to analysing bio-sequences like nucleic acids and proteins are also discussed.

Animals↗