Grammatical Models
نویسنده
چکیده
The Markovian nature follows readily from a mechanistic view, where complete knowledge of a system and sufficient computational resources will allow us to determine the state of the system – or distribution over possible states for stochastic systems – at any given point in the future. Markovian need not progress in time, in fact, for many bioinformatics applications the progression will be in one or more sequences. For example, whether a position in a chromosome is maternally or paternally inherited is quite accurately modelled with a dependency only on whether the previous position was maternally or paternally inherited. In alignments we also commonly assume that the homology of a pair of nucleotides only depends on the homology of the predecessor nucleotides, and not the full alignment. Before continuing it may be informative to remember that not all processes we encounter are Markovian, at least not unless further information is included in the state space. A few examples of this include
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