A compound Poisson model for word occurrences in DNA sequences | Zendy

Robin Stéphane | Zendy

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A compound Poisson model for word occurrences in DNA sequences

Author(s) -

Robin Stéphane

Publication year - 2002

Publication title -

journal of the royal statistical society: series c (applied statistics)

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.205

H-Index - 72

eISSN - 1467-9876

pISSN - 0035-9254

DOI - 10.1111/1467-9876.00279

Subject(s) - poisson distribution , markov chain , sequence (biology) , word (group theory) , set (abstract data type) , poisson process , compound poisson process , computer science , markov model , hidden markov model , markov process , mathematics , algorithm , statistical physics , artificial intelligence , statistics , genetics , physics , biology , geometry , programming language

Summary. We present a compound Poisson model describing the occurrence process of a set of words in a random sequence of letters. The model takes into account the frequency of the words and their overlapping structure. The model is compared with a Markov chain model in terms of fit and parsimony. Special attention is given to the detection of poor or rich regions. Several applications of the model are presented and a combination of the Markov and compound Poisson models is proposed.

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