Phylogenetic analysis of protein sequences based on a novel k-mer natural vector method.
Identifieur interne : 000431 ( Main/Exploration ); précédent : 000430; suivant : 000432Phylogenetic analysis of protein sequences based on a novel k-mer natural vector method.
Auteurs : Yuyan Zhang [République populaire de Chine] ; Jia Wen [République populaire de Chine] ; Stephen S-T Yau [République populaire de Chine]Source :
- Genomics [ 1089-8646 ] ; 2019.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical , chemistry : Viral Proteins, beta-Globins.
- classification : Influenza A virus, Rhinovirus.
- methods : Sequence Analysis, Protein.
- Phylogeny.
Abstract
Based on the k-mer model for protein sequence, a novel k-mer natural vector method is proposed to characterize the features of k-mers in a protein sequence, in which the numbers and distributions of k-mers are considered. It is proved that the relationship between a protein sequence and its k-mer natural vector is one-to-one. Phylogenetic analysis of protein sequences therefore can be easily performed without requiring evolutionary models or human intervention. In addition, there exists no a criterion to choose a suitable k, and k has a great influence on obtaining results as well as computational complexity. In this paper, a compound k-mer natural vector is utilized to quantify each protein sequence. The results gotten from phylogenetic analysis on three protein datasets demonstrate that our new method can precisely describe the evolutionary relationships of proteins, and greatly heighten the computing efficiency.
DOI: 10.1016/j.ygeno.2018.08.010
PubMed: 30195069
Affiliations:
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Electronic address: wenjia198021@126.com.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Information Engineering, Suihua University, Suihua 152061</wicri:regionArea><wicri:noRegion>Suihua 152061</wicri:noRegion></affiliation></author><author><name sortKey="Yau, Stephen S T" sort="Yau, Stephen S T" uniqKey="Yau S" first="Stephen S-T" last="Yau">Stephen S-T Yau</name><affiliation wicri:level="1"><nlm:affiliation>Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China. Electronic address: yau@uic.edu.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Mathematical Sciences, Tsinghua University, Beijing 100084</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></analytic><series><title level="j">Genomics</title><idno type="eISSN">1089-8646</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Influenza A virus (classification)</term><term>Phylogeny</term><term>Rhinovirus (classification)</term><term>Sequence Analysis, Protein (methods)</term><term>Viral Proteins (chemistry)</term><term>beta-Globins (chemistry)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de séquence de protéine ()</term><term>Globines bêta ()</term><term>Phylogénie</term><term>Protéines virales ()</term><term>Rhinovirus ()</term><term>Virus de la grippe A ()</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Viral Proteins</term><term>beta-Globins</term></keywords><keywords scheme="MESH" qualifier="classification" xml:lang="en"><term>Influenza A virus</term><term>Rhinovirus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Sequence Analysis, Protein</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Phylogeny</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de séquence de protéine</term><term>Globines bêta</term><term>Phylogénie</term><term>Protéines virales</term><term>Rhinovirus</term><term>Virus de la grippe A</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Based on the k-mer model for protein sequence, a novel k-mer natural vector method is proposed to characterize the features of k-mers in a protein sequence, in which the numbers and distributions of k-mers are considered. It is proved that the relationship between a protein sequence and its k-mer natural vector is one-to-one. Phylogenetic analysis of protein sequences therefore can be easily performed without requiring evolutionary models or human intervention. In addition, there exists no a criterion to choose a suitable k, and k has a great influence on obtaining results as well as computational complexity. In this paper, a compound k-mer natural vector is utilized to quantify each protein sequence. The results gotten from phylogenetic analysis on three protein datasets demonstrate that our new method can precisely describe the evolutionary relationships of proteins, and greatly heighten the computing efficiency.</div></front></TEI><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Pékin</li></settlement></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Zhang, Yuyan" sort="Zhang, Yuyan" uniqKey="Zhang Y" first="Yuyan" last="Zhang">Yuyan Zhang</name></noRegion><name sortKey="Wen, Jia" sort="Wen, Jia" uniqKey="Wen J" first="Jia" last="Wen">Jia Wen</name><name sortKey="Yau, Stephen S T" sort="Yau, Stephen S T" uniqKey="Yau S" first="Stephen S-T" last="Yau">Stephen S-T Yau</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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