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Prediction of complete gene structures in human genomic DNA.
We introduce a general probabilistic model of the gene structure of human genomic sequences which incorporates descriptions of the basic transcriptional, translational and splicing signals, as well…
A second course in stochastic processes
Preface. Preface to A First Course. Preface to First Edition. Contents of A First Course. Algebraic Methods in Markov Chains. Ratio Theorems of Transition Probabilities and Applications. Sums of…
A First Course on Stochastic Processes
The Basic Limit Theorem of Markov Chains and Applications and Classical Examples of Continuous Time Markov chains are presented.
Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes.
Using an appropriate random model, this work presents a theory that provides precise numerical formulas for assessing the statistical significance of any region with high aggregate score and examples are given of applications to a variety of protein sequences, highlighting segments with unusual biological features.
Tchebycheff Systems: With Applications in Analysis and Statistics.
Classes of orderings of measures and related correlation inequalities. I. Multivariate totally positive distributions
The differential equations of birth-and-death processes, and the Stieltjes moment problem
Pi,i+i(t) = Xit + o(t), Pi,i(t) = 1 (Xi + ,Yi)t + 0(t), Pi,i_i(t) = pit + o(t), as t->O, where Xi, pui are constants which may be thought of as the rates of absorption from state i into states i+1,…
Embedding of Urn Schemes into Continuous Time Markov Branching Processes and Related Limit Theorems
Dinucleotide relative abundance extremes: a genomic signature.