Statistical tools for discovering pseudo-periodicities in biological sequences

Bernard Prum; Élisabeth de Turckheim; Martin Vingron

ESAIM: Probability and Statistics (2010)

  • Volume: 5, page 171-181
  • ISSN: 1292-8100

Abstract

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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.

How to cite

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Prum, Bernard, de Turckheim, Élisabeth, and Vingron, Martin. "Statistical tools for discovering pseudo-periodicities in biological sequences." ESAIM: Probability and Statistics 5 (2010): 171-181. <http://eudml.org/doc/197759>.

@article{Prum2010,
abstract = {
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. },
author = {Prum, Bernard, de Turckheim, Élisabeth, Vingron, Martin},
journal = {ESAIM: Probability and Statistics},
keywords = {Biological sequences; proteins; periodicity; autocovariance funtion.},
language = {eng},
month = {3},
pages = {171-181},
publisher = {EDP Sciences},
title = {Statistical tools for discovering pseudo-periodicities in biological sequences},
url = {http://eudml.org/doc/197759},
volume = {5},
year = {2010},
}

TY - JOUR
AU - Prum, Bernard
AU - de Turckheim, Élisabeth
AU - Vingron, Martin
TI - Statistical tools for discovering pseudo-periodicities in biological sequences
JO - ESAIM: Probability and Statistics
DA - 2010/3//
PB - EDP Sciences
VL - 5
SP - 171
EP - 181
AB - 
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.
LA - eng
KW - Biological sequences; proteins; periodicity; autocovariance funtion.
UR - http://eudml.org/doc/197759
ER -

References

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