2012/07 | LEM Working Paper Series | |
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Detecting Correlations among Functional Sequence Motifs |
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Davide Pirino, Jacopo Rigosa, Alice Ledda, Luca Ferretti |
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JEL Classifications | ||
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C00, C02
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Abstract | ||
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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.
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