title: Construction of stochastic context trees for genetic texts.
abstract: A method has been developed for constructing a tree source model for genetic text generation. Model visualisation in the form of suffix (context) trees provides a new way of context analysis of symbol sequences. Estimation of the stochastic complexity of the data in the frame of the model serves as a criterion for the model's ascertainment. The model and complexity values are used for analysis of genetic texts. The software realisation of this algorithm enables to reveal statistical properties of genetic sequences based on an information measure. The program developed is available via Internet at http://wwwmgs.bionet.nsc.ru/mgs/programs/complexity/.
authors.affiliation: Institute of Cytology and Genetics SB RAS, Acad Lavrentiev ave., 10, Novosibirsk, 630090, Russia. orlov@bionet.nsc.ru
authors.forename: Yury L
authors.initials: YL
authors.lastname: Orlov
authors.forename: Vladimir P
authors.initials: VP
authors.lastname: Filippov
authors.forename: Vladimir N
authors.initials: VN
authors.lastname: Potapov
authors.forename: Nikolay A
authors.initials: NA
authors.lastname: Kolchanov
mesh_terms: D004247:DNA / Q000235:genetics; D008390:Markov Chains; D008957:Models, Genetic; D011506:Proteins / Q000235:genetics; D017422:Sequence Analysis, DNA; D012984:Software
chemical_list: D011506:Proteins; D004247:DNA