Introduction. The context -- Randomness and models -- A bit of biology -- Simple models for biological sequences. Why a model? -- Permutation model -- Bernoulli model -- Introduction to Markov chain models. Assumptions -- Markov chain order 1 -- Markov chain order m -- Estimation of the parameters -- Taking heterogeneities into account. Phased chains -- Piecewise homogeneous Markov chains -- Translation conditional models -- Statistical properties of word occurrences. Count -- Positions and distances -- Distribution along the sequence -- Words with unexpected frequencies. Exact distribution and approximations -- Influence of the model -- Over-representations of Chi sites in E. coli and H. influenzae -- Under-representation of palindromes of length 6 in E. coli and in the phage Lambda -- Words with unexpected locations. Chi sites in the genome of H. influenzae -- Distribution of palindromes in E. coli's genome -- Detection of promoter sites in B. subtilis -- The last word.