SMILE

Stochastic Models for the Inference of Life Evolution

Bibtex

@article{pirino_detecting_2012,
Author = {Pirino, Davide and Rigosa, Jacopo and Ledda, Alice and
Ferretti, Luca},
Title = {Detecting correlations among functional-sequence
motifs},
Journal = {Physical Review E},
Volume = {85},
Number = {6 Pt 2},
Pages = {066124},
abstract = {Sequence motifs are words of nucleotides in DNA with
biological functions, e.g., gene regulation.
Identification of such words proceeds through rejection
of Markov models on the expected motif frequency along
the genome. Additional biological information can be
extracted from the correlation structure among patterns
of motif occurrences. In this paper a log-linear
multivariate intensity Poisson model is estimated via
expectation maximization on a set of motifs along the
genome of E. coli K12. The proposed approach allows for
excitatory as well as inhibitory interactions among
motifs and between motifs and other genomic features
like gene occurrences. Our findings confirm previous
stylized facts about such types of interactions and
shed new light on genome-maintenance functions of some
particular motifs. We expect these methods to be
applicable to a wider set of genomic features.},
doi = {10.1103/PhysRevE.85.066124},
issn = {1550-2376},
language = {eng},
month = jun,
pmid = {23005179},
year = 2012
}