Biomedical subjects

M Dauchet

Publications and source records attributed to M Dauchet.

3 recordsLinked to original sources

PubMed1999

Location of repetitive regions in sequences by optimizing a compression method.

Suppose that a biologist wishes to study some local property P of genetic sequences. If he can design (with a computer scientist) an algorithm C which efficiently compresses parts of the sequence which satisfy P, then our algorithm TurboOptLift locates very quickly where property P occurs by chance on a sequence, and where it occurs as a result of a significant process. Under some conditions, the time complexity of TurboOptLift is O(n log n). We illustrate its use on the practical problem of locating approximate tandem repeats in DNA sequences.

Algorithms↗

PubMed1997

Detection of significant patterns by compression algorithms: the case of approximate tandem repeats in DNA sequences.

MOTIVATION: Compression algorithms can be used to analyse genetic sequences. A compression algorithm tests a given property on the sequence and uses it to encode the sequence: if the property is true, it reveals some structure of the sequence which can be described briefly, this yields a description of the sequence which is shorter than the sequence of nucleotides given in extenso. The more a sequence is compressed by the algorithm, the more significant is the property for that sequence. RESULTS: We present a compression algorithm that tests the presence of a particular type of dosDNA (defined ordered sequence-DNA): approximate tandem repeats of small motifs (i.e. of lengths < 4). This algorithm has been experimented with on four yeast chromosomes. The presence of approximate tandem repeats seems to be a uniform structural property of yeast chromosomes.

Algorithms↗

PubMed1996

Compression and genetic sequence analysis.

A novel approach to genetic sequence analysis is presented. This approach, based on compression of algorithms, has been launched simultaneously by Grumbach and Tahi, Milosavljevic and Rivals. To reduce the description of an object, a compression algorithm replaces some regularities in the description by special codes. Thus a compression algorithm can be applied to a sequence in order to study the presence of those regularities all over the sequence. This paper explains this ability, gives examples of compression algorithms already developed and mentions their applications. Finally, the theoretical foundations of the approach are presented in an overview of the algorithmic theory of information.

Algorithms↗