The Z curve database: a graphic representation of genome sequences

Motivation: Genome projects for many prokaryotic and eukaryotic species have been completed and more new genome projects are being underway currently. The availability of a large number of genomic sequences for researchers creates a need to find graphic tools to study genomes in a perceivable form....

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Veröffentlicht in:Bioinformatics 2003-03, Vol.19 (5), p.593-599
Hauptverfasser: Zhang, Chun-Ting, Zhang, Ren, Ou, Hong-Yu
Format: Artikel
Sprache:eng
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Zusammenfassung:Motivation: Genome projects for many prokaryotic and eukaryotic species have been completed and more new genome projects are being underway currently. The availability of a large number of genomic sequences for researchers creates a need to find graphic tools to study genomes in a perceivable form. The Z curve is one of such tools available for visualizing genomes. The Z curve is a unique three-dimensional curve representation for a given DNA sequence in the sense that each can be uniquely reconstructed given the other. The Z curve database for more than 1000 genomes have been established here. Results: The database contains the Z curves for archaea, bacteria, eukaryota, organelles, phages, plasmids, viroids and viruses, whose genomic sequences are currently available. All the 3-dimensional Z curves and their three component curves are stored in the database. The applications of the Z curve database on comparative genomics, gene prediction, computation of G+C content with a windowless technique, prediction of replication origins and terminations of bacterial and archaeal genomes and study of local deviations from the Chargaff Parity Rule 2 etc. are presented in detail. The Z curve database reported here is a treasure trove in which biologists could find useful biological knowledge. Availability: The Z curve database is freely available at the website: http://tubic.tju.edu.cn/zcurve/ Contact: ctzhang@tju.edu.cn * To whom correspondence should be addressed.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btg041