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Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.

Identifieur interne : 002552 ( PubMed/Curation ); précédent : 002551; suivant : 002553

Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.

Auteurs : Tiee-Jian Wu [Taïwan] ; Ying-Hsueh Huang ; Lung-An Li

Source :

Bioinformatics (Oxford, England) [ 1367-4803 ] ; 2005.

RBID : pubmed:16144805

Descripteurs français

English descriptors

KwdEn :
- Algorithms, Computational Biology (methods), Computer Simulation, Computers, DNA (chemistry), Databases, Genetic, Databases, Protein, Escherichia coli (genetics), Genes, Bacterial, Genome, Humans, Lipoprotein Lipase (genetics), Models, Genetic, Models, Statistical, Oligonucleotide Array Sequence Analysis, Oligonucleotide Probes (chemistry), Open Reading Frames, Pattern Recognition, Automated, Phylogeny, SARS Virus (genetics), Sequence Analysis, DNA (methods), Shigella flexneri (genetics), Software, Species Specificity.
MESH :
- chemical , chemistry : DNA, Oligonucleotide Probes.
- genetics : Escherichia coli, Lipoprotein Lipase, SARS Virus, Shigella flexneri.
- methods : Computational Biology, Sequence Analysis, DNA.
- Algorithms, Computer Simulation, Computers, Databases, Genetic, Databases, Protein, Genes, Bacterial, Genome, Humans, Models, Genetic, Models, Statistical, Oligonucleotide Array Sequence Analysis, Open Reading Frames, Pattern Recognition, Automated, Phylogeny, Software, Species Specificity.

Abstract

Several measures of DNA sequence dissimilarity have been developed. The purpose of this paper is 3-fold. Firstly, we compare the performance of several word-based or alignment-based methods. Secondly, we give a general guideline for choosing the window size and determining the optimal word sizes for several word-based measures at different window sizes. Thirdly, we use a large-scale simulation method to simulate data from the distribution of SK-LD (symmetric Kullback-Leibler discrepancy). These simulated data can be used to estimate the degree of dissimilarity beta between any pair of DNA sequences.

DOI: 10.1093/bioinformatics/bti658
PubMed: 16144805

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Le document en format XML

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<author><name sortKey="Wu, Tiee Jian" sort="Wu, Tiee Jian" uniqKey="Wu T" first="Tiee-Jian" last="Wu">Tiee-Jian Wu</name>
<affiliation wicri:level="1"><nlm:affiliation>Department of Statistics, National Cheng-Kung University, Tainan, Taiwan. tjwu@stat.ncku.edu.tw</nlm:affiliation>
<country xml:lang="fr">Taïwan</country>
<wicri:regionArea>Department of Statistics, National Cheng-Kung University, Tainan</wicri:regionArea>
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<author><name sortKey="Huang, Ying Hsueh" sort="Huang, Ying Hsueh" uniqKey="Huang Y" first="Ying-Hsueh" last="Huang">Ying-Hsueh Huang</name>
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<author><name sortKey="Li, Lung An" sort="Li, Lung An" uniqKey="Li L" first="Lung-An" last="Li">Lung-An Li</name>
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<term>DNA (chemistry)</term>
<term>Databases, Genetic</term>
<term>Databases, Protein</term>
<term>Escherichia coli (genetics)</term>
<term>Genes, Bacterial</term>
<term>Genome</term>
<term>Humans</term>
<term>Lipoprotein Lipase (genetics)</term>
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<term>Models, Statistical</term>
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<term>SARS Virus (genetics)</term>
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<term>Shigella flexneri (genetics)</term>
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<term>Species Specificity</term>
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<keywords scheme="KwdFr" xml:lang="fr"><term>ADN ()</term>
<term>Algorithmes</term>
<term>Analyse de séquence d'ADN ()</term>
<term>Bases de données de protéines</term>
<term>Bases de données génétiques</term>
<term>Biologie informatique ()</term>
<term>Cadres ouverts de lecture</term>
<term>Escherichia coli (génétique)</term>
<term>Gènes bactériens</term>
<term>Génome</term>
<term>Humains</term>
<term>Lipoprotein lipase (génétique)</term>
<term>Logiciel</term>
<term>Modèles génétiques</term>
<term>Modèles statistiques</term>
<term>Ordinateurs</term>
<term>Phylogénie</term>
<term>Reconnaissance automatique des formes</term>
<term>Shigella flexneri (génétique)</term>
<term>Simulation numérique</term>
<term>Sondes oligonucléotidiques ()</term>
<term>Spécificité d'espèce</term>
<term>Séquençage par oligonucléotides en batterie</term>
<term>Virus du SRAS (génétique)</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>DNA</term>
<term>Oligonucleotide Probes</term>
</keywords>
<keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Escherichia coli</term>
<term>Lipoprotein Lipase</term>
<term>SARS Virus</term>
<term>Shigella flexneri</term>
</keywords>
<keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Escherichia coli</term>
<term>Lipoprotein lipase</term>
<term>Shigella flexneri</term>
<term>Virus du SRAS</term>
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<keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term>
<term>Sequence Analysis, DNA</term>
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<keywords scheme="MESH" xml:lang="en"><term>Algorithms</term>
<term>Computer Simulation</term>
<term>Computers</term>
<term>Databases, Genetic</term>
<term>Databases, Protein</term>
<term>Genes, Bacterial</term>
<term>Genome</term>
<term>Humans</term>
<term>Models, Genetic</term>
<term>Models, Statistical</term>
<term>Oligonucleotide Array Sequence Analysis</term>
<term>Open Reading Frames</term>
<term>Pattern Recognition, Automated</term>
<term>Phylogeny</term>
<term>Software</term>
<term>Species Specificity</term>
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<term>Algorithmes</term>
<term>Analyse de séquence d'ADN</term>
<term>Bases de données de protéines</term>
<term>Bases de données génétiques</term>
<term>Biologie informatique</term>
<term>Cadres ouverts de lecture</term>
<term>Gènes bactériens</term>
<term>Génome</term>
<term>Humains</term>
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<term>Reconnaissance automatique des formes</term>
<term>Simulation numérique</term>
<term>Sondes oligonucléotidiques</term>
<term>Spécificité d'espèce</term>
<term>Séquençage par oligonucléotides en batterie</term>
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<front><div type="abstract" xml:lang="en">Several measures of DNA sequence dissimilarity have been developed. The purpose of this paper is 3-fold. Firstly, we compare the performance of several word-based or alignment-based methods. Secondly, we give a general guideline for choosing the window size and determining the optimal word sizes for several word-based measures at different window sizes. Thirdly, we use a large-scale simulation method to simulate data from the distribution of SK-LD (symmetric Kullback-Leibler discrepancy). These simulated data can be used to estimate the degree of dissimilarity beta between any pair of DNA sequences.</div>
</front>
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<DateCompleted><Year>2006</Year>
<Month>01</Month>
<Day>25</Day>
</DateCompleted>
<DateRevised><Year>2005</Year>
<Month>11</Month>
<Day>04</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">1367-4803</ISSN>
<JournalIssue CitedMedium="Print"><Volume>21</Volume>
<Issue>22</Issue>
<PubDate><Year>2005</Year>
<Month>Nov</Month>
<Day>15</Day>
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<Title>Bioinformatics (Oxford, England)</Title>
<ISOAbbreviation>Bioinformatics</ISOAbbreviation>
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<ArticleTitle>Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.</ArticleTitle>
<Pagination><MedlinePgn>4125-32</MedlinePgn>
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<Abstract><AbstractText Label="MOTIVATION" NlmCategory="BACKGROUND">Several measures of DNA sequence dissimilarity have been developed. The purpose of this paper is 3-fold. Firstly, we compare the performance of several word-based or alignment-based methods. Secondly, we give a general guideline for choosing the window size and determining the optimal word sizes for several word-based measures at different window sizes. Thirdly, we use a large-scale simulation method to simulate data from the distribution of SK-LD (symmetric Kullback-Leibler discrepancy). These simulated data can be used to estimate the degree of dissimilarity beta between any pair of DNA sequences.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">Our study shows (1) for whole sequence similiarity/dissimilarity identification the window size taken should be as large as possible, but probably not >3000, as restricted by CPU time in practice, (2) for each measure the optimal word size increases with window size, (3) when the optimal word size is used, SK-LD performance is superior in both simulation and real data analysis, (4) the estimate beta of beta based on SK-LD can be used to filter out quickly a large number of dissimilar sequences and speed alignment-based database search for similar sequences and (5) beta is also applicable in local similarity comparison situations. For example, it can help in selecting oligo probes with high specificity and, therefore, has potential in probe design for microarrays.</AbstractText>
<AbstractText Label="AVAILABILITY" NlmCategory="BACKGROUND">The algorithm SK-LD, estimate beta and simulation software are implemented in MATLAB code, and are available at http://www.stat.ncku.edu.tw/tjwu</AbstractText>
</Abstract>
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<ForeName>Tiee-Jian</ForeName>
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Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.

Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences.

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

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