Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1188053 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Profiling subclonal architecture and phylogeny in tumors by whole-genome sequence data mining and single-cell genome sequencing
| EGAS00001001145 | EGA
Project description:Profiling subclonal architecture and phylogeny in tumors by whole-genome sequence data mining and single-cell genome sequencing
| EGAD00001001429 | EGA
Project description:Genotyping studies suggest that there is genetic variability among P. gingivalis strains, however the extent of variability remains unclear, and the regions of variability have only partially been identified. We previously used heteroduplex analysis of the ribosomal operon intergenic spacer region (ISR) to type P. gingivalis strains in several diverse populations, identifying 6 predominant heteroduplex types and many minor ones. In addition we used ISR sequence analysis to determine the relatedness of P. gingivalis strains to one another, and demonstrated a link between ISR sequence phylogeny and the disease-associated phenotype of P. gingivalis strains. The availability of whole genome microarrays based on the genomic sequence of strain W83 has allowed a more comprehensive analysis of P. gingivalis strain variability, using the entire genome. The objectives of this study were to define the phylogeny of P. gingivalis strains using the entire genome, to compare the phylogeny based on genome content to the phylogeny based on a single locus (ISR), and to identify genes that are associated with the strongly disease-associated strain W83 that could be important for virulence. Keywords: Comparative genomic hybridization
2008-10-09 | GSE13128 | GEO
Project description:We extended the mathematical models of measuring biodiversity to estimate DNA methylation heterogeneity in a cell population. We propose a model-based approach (abundance-based, phylogeny-based and pairwise similarity-based heterogeneity) and consider similarity in DNA methylation patterns from individual cells to evaluate heterogeneity that overcomes biases due to missing data. We also applied commonly used non-model based method (methylation entropy) and other reported methods of estimating methylation heterogeneity such as single-cell based approach to evaluate methylation heterogeineity.
2017-09-15 | GSE103859 | GEO
Project description:Genotyping studies suggest that there is genetic variability among P. gingivalis strains, however the extent of variability remains unclear, and the regions of variability have only partially been identified. We previously used heteroduplex analysis of the ribosomal operon intergenic spacer region (ISR) to type P. gingivalis strains in several diverse populations, identifying 6 predominant heteroduplex types and many minor ones. In addition we used ISR sequence analysis to determine the relatedness of P. gingivalis strains to one another, and demonstrated a link between ISR sequence phylogeny and the disease-associated phenotype of P. gingivalis strains. The availability of whole genome microarrays based on the genomic sequence of strain W83 has allowed a more comprehensive analysis of P. gingivalis strain variability, using the entire genome. The objectives of this study were to define the phylogeny of P. gingivalis strains using the entire genome, to compare the phylogeny based on genome content to the phylogeny based on a single locus (ISR), and to identify genes that are associated with the strongly disease-associated strain W83 that could be important for virulence. Keywords: Comparative genomic hybridization Comparative genomic analysis of 7 clinically prevalent P. gingivalis strains was performed, using whole genome microarrays based on the sequence of strain W83. Strain W83 was the reference strains and there were 6 test strains. Flip-dye replicates were performed.
2010-05-18 | E-GEOD-13128 | biostudies-arrayexpress
Project description:Based on our previous O-Search strategy, we have developed a new search method, O-Search-Pattern, to process searching for O-glycopeptide. In comparison of analyzing our human serum dataset generated from optimized energy, our new method can generate more GPSMs glycopeptide sequences than currently state-of-the-art search tools.
2023-05-31 | PXD039079 | JPOST Repository
Project description:Molecular networking and pattern-based genome mining improves discovery of biosynthetic gene clusters and their products from Salinispora
2016-01-27 | MSV000079484 | GNPS
Project description:Genome-wide SNP genotyping array can genotyped SNP highthroughly. It can be used in many aspects, such as phylogeny relationships, genome-wide association studies, copy number identification.
2013-05-09 | GSE46733 | GEO
Project description:LCMS analysis of LC-purified lomaiviticin C - Reference: Kersten, R.D., Lane, A.L., Nett, M., Richter, T.K., Duggan, B.M., Dorrestein, P.C., Moore, B.S. Bioactivity-Guided Genome Mining Reveals the Lomaiviticin Biosynthetic Gene Cluster in Salinispora tropica. Chembiochem 14, 955-962 (2013).
2014-05-22 | MSV000078665 | GNPS