Many protein sequences present non trivial periodicities, such as cysteine signatures and leucine heptads. These known periodicities probably represent a small percentage of the total number of sequences periodic structures, and it is useful to have general tools to detect such sequences and their period in large databases of sequences. We compare three statistics adapted from those used in time series analysis: a generalisation of the simple autocovariance based on a similarity score and two statistics intending to increase the power of the method. Theoretical behaviour of these statistics are derived, and the corresponding tests are then described. In this paper we also present an application of these tests to a protein known to have sequence periodicity.
Mots clés : biological sequences, proteins, periodicity, autocovariance funtion
@article{PS_2001__5__171_0, author = {Prum, Bernard and Turckheim, \'Elisabeth de and Vingron, Martin}, title = {Statistical tools for discovering pseudo-periodicities in biological sequences}, journal = {ESAIM: Probability and Statistics}, pages = {171--181}, publisher = {EDP-Sciences}, volume = {5}, year = {2001}, mrnumber = {1875669}, zbl = {0992.62099}, language = {en}, url = {http://www.numdam.org/item/PS_2001__5__171_0/} }
TY - JOUR AU - Prum, Bernard AU - Turckheim, Élisabeth de AU - Vingron, Martin TI - Statistical tools for discovering pseudo-periodicities in biological sequences JO - ESAIM: Probability and Statistics PY - 2001 SP - 171 EP - 181 VL - 5 PB - EDP-Sciences UR - http://www.numdam.org/item/PS_2001__5__171_0/ LA - en ID - PS_2001__5__171_0 ER -
%0 Journal Article %A Prum, Bernard %A Turckheim, Élisabeth de %A Vingron, Martin %T Statistical tools for discovering pseudo-periodicities in biological sequences %J ESAIM: Probability and Statistics %D 2001 %P 171-181 %V 5 %I EDP-Sciences %U http://www.numdam.org/item/PS_2001__5__171_0/ %G en %F PS_2001__5__171_0
Prum, Bernard; Turckheim, Élisabeth de; Vingron, Martin. Statistical tools for discovering pseudo-periodicities in biological sequences. ESAIM: Probability and Statistics, Tome 5 (2001), pp. 171-181. http://www.numdam.org/item/PS_2001__5__171_0/
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