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Start Over Author "Jumamurat R. Bayjanov" Journal bioinformatics
3 results on '"Jumamurat R. Bayjanov"'

1. PanCGH: a genotype-calling algorithm for pangenome CGH data

Author

Johan E. T. van Hylckama Vlieg, Michiel Wels, Roland J. Siezen, Jumamurat R. Bayjanov, Douwe Molenaar, Marjo J. C. Starrenburg, and Molecular Cell Physiology

Subjects
Statistics and Probability, Genotype, Energy and redox metabolism [NCMLS 4], Biology, Biochemistry, Genome, Evolution, Molecular, Genetic variation, Cluster Analysis, Genetic variability, Databases, Protein, Molecular Biology, Gene, Genetics, Genetic diversity, Comparative Genomic Hybridization, DNA–DNA hybridization, Computational Biology, Genetic Variation, Original Papers, Computer Science Applications, Phylogenetics, Computational Mathematics, Computational Theory and Mathematics, Algorithm, Algorithms, Genome, Bacterial, Comparative genomic hybridization
Abstract

Motivation: Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data. Results: We have developed the algorithm PanCGH that incorporates orthology information about genes to predict the presence or absence of orthologous genes in a query organism using CGH arrays that target the genomes of sequenced representatives of a group of microorganisms. PanCGH was tested and applied in the analysis of genetic diversity among 39 Lactococcus lactis strains from three different subspecies (lactis.cremoris, hordniae) and isolated from two different niches (dairy and plant). Clustering of these strains using the presence/absence data of gene orthologs revealed a clear separation between different subspecies and reflected the niche of the strains. Contact: J.Bayjanov@cmbi.ru.nl Supplementary information: Supplementary data are available at Bioinformatics online.

Published
2009
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2. PanCGHweb: a web tool for genotype calling in pangenome CGH data

Author

Roland J. Siezen, Sacha A. F. T. van Hijum, and Jumamurat R. Bayjanov

Subjects
Statistics and Probability, Energy and redox metabolism [NCMLS 4], Genotype, Genomics, Biology, Biochemistry, Genome, Web tool, Open Reading Frames, Molecular Biology, Phylogeny, Oligonucleotide Array Sequence Analysis, Genetics, Internet, Models, Genetic, Microarray analysis techniques, Comparative Genome Hybridization, Computational Biology, Genetic Variation, Nucleic Acid Hybridization, Sequence Analysis, DNA, Computer Science Applications, Phylogenetics, Lactococcus lactis, Computational Mathematics, Applications Note, Computational Theory and Mathematics, DNA microarray, Algorithms, Software
Abstract

Summary: A pangenome is the total of genes present in strains of the same species. Pangenome microarrays allow determining the genomic content of bacterial strains more accurately than conventional comparative genome hybridization microarrays. PanCGHweb is the first tool that effectively calls genotype based on pangenome microarray data. Availability: PanCGHweb, the web tool is accessible from: http://bamics2.cmbi.ru.nl/websoftware/pancgh/ Contact: sacha.vanhijum@nizo.nl

Published
2010

3. PanCGH: a genotype-calling algorithm for pangenome CGH data.

Author

Jumamurat R. Bayjanov, Michiel Wels, Marjo Starrenburg, Johan E. T. van Hylckama Vlieg, Roland J. Siezen, and Douwe Molenaar

Subjects
COMPARATIVE genomic hybridization, ALGORITHMS, BIOINFORMATICS, NUCLEOTIDE sequence, OLIGOMERS, MICROBIOLOGY, GENETIC polymorphisms
Abstract

Motivation: Pangenome arrays contain DNA oligomers targeting several sequenced reference genomes from the same species. In microbiology, these can be employed to investigate the often high genetic variability within a species by comparative genome hybridization (CGH). The biological interpretation of pangenome CGH data depends on the ability to compare strains at a functional level, particularly by comparing the presence or absence of orthologous genes. Due to the high genetic variability, available genotype-calling algorithms can not be applied to pangenome CGH data. Results: We have developed the algorithm PanCGH that incorporates orthology information about genes to predict the presence or absence of orthologous genes in a query organism using CGH arrays that target the genomes of sequenced representatives of a group of microorganisms. PanCGH was tested and applied in the analysis of genetic diversity among 39 Lactococcus lactis strains from three different subspecies (lactis.cremoris, hordniae) and isolated from two different niches (dairy and plant). Clustering of these strains using the presence/absence data of gene orthologs revealed a clear separation between different subspecies and reflected the niche of the strains. Contact: J.Bayjanov@cmbi.ru.nl Supplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2009
Full Text
View/download PDF

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