Sentences with phrase «genome analysis data»

The Pseudomonas Genome Database collaborates with an international panel of expert Pseudomonas researchers to provide high quality updates to the PAO1 genome annotation and make cutting edge genome analysis data available

Not exact matches

By increasing the speed and accuracy for NGS data analysis like whole genome sequencing (WGS), our computing platform makes it easier to discover links between DNA sequence variations and human disease.»

Their analysis of data in previous studies done by The Cancer Genome Atlas group have shown that the types of abnormal methylation levels they found are lower in smokers who have quit for more than 10 years than those who have not quit.

The pitfalls of statistical analysis In the new investigation, Wörheide and his colleagues reanalyzed the genome data reported in the earlier studies, and their results reject the «Ctenophora first» hypothesis.

The following Berkeley Lab researchers also contributed to the study: Benjamin Bowen, a member of Northen's lab in EGSB and at the Joint Genome Institute, a DOE Office of Science User Facility, helped analyze metabolomics data; Ulas Karaoz in the Earth and Environmental Sciences Area (EESA) analyzed metagenomics data; and Joel Swenson, a former postdoctoral researcher in Biosciences» Biological Systems and Engineering Division, helped conduct correlation and statistical analyses.

Comprehensive genome analysis: more than 85,000 participants from 35 studies Under the direction of the National Institute of Environmental Health Sciences in the United States, the team of international scientists analyzed the data from a total of 85,170 participants from 35 study cohorts.

These genomic variations have been revealed by studies in the population and by analysis of the genomes of colon cancer patients that are available in data bases such as that of the 1000 Genomes Projecgenomes of colon cancer patients that are available in data bases such as that of the 1000 Genomes Project Ddata bases such as that of the 1000 Genomes ProjecGenomes Project DataData.

Among other initiatives, his group contributes to ENCODE (Encyclopedia of DNA Elements), supported by NIH to define functional genomic elements; the DOE Systems Biology Knowledgebase (KBase) for data sharing and analysis; and the internationally funded 1000 Genomes Project on human genetic variation.

Professor Ed Feil, joint lead author from the Milner Centre for Evolution, at the University of Bath, said: «We've developed user - friendly analysis software that demonstrates how whole genome sequence data can be a powerful tool for pan-European surveillance of MRSA and other important pathogens.

Commenting on the survey results, David Lipman, director of the US National Center for Biotechnology Information in Bethesda, Maryland, says that the worries about data handling and analysis were an issue even in the earliest discussions of the genome project.

Currently, the mainstream applications are the management of heterogeneous biological data and genome analysis.

Through more than 1,600 separate experiments, analysis of more than 140 cell types and a massive amount of data analysis, the group found about 4 million of these so - called switches and can now assign functions to more than 80 percent of the entire genome.

In their work, Dr. Lessnick and his team used bioinformatics analysis of experimental data in an unbiased genome - wide approach.

He was part of a team applying new methods of data analysis on previously studied genomes, and initially thought the unexpected DNA was a glitch.

Researchers expect the data presented in this study to fuel the formation of large national and international research consortiums to conduct comprehensive, systematic analysis of inherited (germline) genome data in large cohorts of uveal melanoma patients.

Added Robert Fulton, director of technology development at Washington University's McDonnell Genome Institute, which contributed to the sequencing and analysis of the data: «This research is a great example of the value of comprehensive genomic analyses and the insights that can be gained from thorough, well - designed studies.

To better determine the history of modern birds, we performed a genome - scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome - scale data.

To facilitate the resulting data analysis, the researchers in Bielefeld and their colleagues in this project applied a completely new procedure that sorts the single chromosomes of the genome.

Tested on data from The Cancer Genome Atlas (TCGA), MEGENA identified novel regulatory targets in breast and lung cancers, outperforming other co-expression analysis methods.

HM - SNS allows researchers to sequence the genomes of single tumor cells and study multiple cells simultaneously, both lowering the cost and boosting data analysis for such studies.

Using technologies like whole genome or whole exome (the protein - coding portion of the genome) sequencing requires specialized equipment and advanced data analysis and is still relatively expensive.

The second tool, SuperExactTest, establishes the very first theoretical framework for assessing the statistical significance of multi-set intersections and enables users to compare very large sets of data, such as gene sets produced from genome - wide association studies (GWAS) and differential expression analysis.

«Using the genome data analysis methods developed by co-author Steve Horvath at UCLA, we have uncovered crucial gene networks and we can now predict possible future genetic disorders at the eight - cell stage.»

This achievement marks the first big test of a new analysis method that can speed up genome assembly by compressing the raw sequence data 100-fold.

Together, all five RMs serve as a collection of well - characterized, whole genome standards that can tell a laboratory how well its DNA sequencing processes are working by measuring the performance of the equipment, chemistry and data analysis involved.

«Some analyses of the ENCODE data alone have argued that upwards of 80 % of the genome is functional, but our evolutionary analysis suggests that isn't the case.»

With their analyses of the genome data, the scientists were also able to identify eight specific gene variants that are strongly linked to altered risk for both diseases.

The Human Genome Project so increased the speed with which researchers can generate data that the bottleneck no longer lies in data generation but in data analysis.

These include two flagship papers: one exploiting genomic - scale data to generate a highly supported avian order phylogeny that resolves many debates on the timing and topology of their radiation; the other a comparative genomic analysis exploring avian genome evolution and the genetic basis of complex traits.

This HDG genome represented the most complete de novo genome assembly to date, and with other omics data resources available from this individual, the work can be used as a benchmark for developing new sequencing and assembly techniques, and for functional studies involving RNA or protein analysis.

We therefore performed unsupervised clustering analyses with ADMIXTURE (SNP array data; Supplementary Fig. 15) and NGSadmix (whole - genome data; Fig. 4 and Supplementary Fig. 16)(Supplementary Note 9) and found that, unlike contemporary European village dogs, all three ancient genomes possess a significant ancestry component that is present in modern Southeast Asian dogs.

High throughput genome sequencing and quantitative image analysis provide evolution, metabolic, and interaction data to build community metabolome maps, taxa / gene networks, and spatial ecosystem models.

The assembly and analysis of human tumor cell genomes, many of which contain chromosome deletions, duplications and insertions, as well as single nucleotide changes, requires immense data storage capacity and high - speed computation.

By probit analysis, the 95 % limit of detection for TMAdV was 781, 377, or 35 viral genome equivalents / mL for serum, stool, or oral swab samples, respectively (data not shown).

Scientists for years have looked for the biological roots of the problem using tools such as genome - wide association studies and gene - linkage analysis, which crunch genetic and health data from thousands of people in an effort to pinpoint disease - causing genetic variants.

Bootscanning analysis was initially performed with all 95 unique, fully - sequenced adenovirus genomes in GenBank (data not shown).

Data included community composition by 16S rRNA gene iTag analysis and metaproteomic analysis of partially purified fractions of the community proteome that catalyzed toluene biosynthesis from phenylacetic acid; proteins were identified by mapping peptides to a community metagenome (Joint Genome Institute IMG Taxon ID 3300001784).

The initial version of CRI iAtlas is based on an analysis performed by The Cancer Genome Atlas (TCGA) Research Network on the TCGA data set comprising over 10,000 tumor samples and 33 tumor samples (Thorsson et al..

ENSEMBL makes available substantial and diverse transcript information, including the CCDS [13, 41], Human and Vertebrate Analysis and Annotation (HAVANA)[42], Vertebrate Genome Annotation (Vega)[43], ENCODE data [12] and the GENCODE gene and transcript sets [15].

The most significant of these was the HiSeq X Ten, a 10 - instrument «factory installation» that enabled the most cost - effective human whole genome sequencing to date: 18,000 genomes per year at a consumables cost of just over $ 1,000 each (note: this does not include the costs of data storage, analysis, or the $ 10 million buy - in).

James Giovannoni generated the gene expression data through RNA - sequencing and Lukas Mueller provided additional analysis to confirm the quality of the genome assembly.

Based at the Wellcome Trust Sanger Institute, Magnus works on the scientific analysis of high - throughput genome sequencing data for MalariaGEN, primarily on pathogen projects.

conduct computational meta - analyses on large, aggregated cancer genome data sets to identify the long tail of infrequently mutated cancer genes, to characterise mutational signatures and to inform on the evolution of cancer cell clones.

As an example, the ICGC / TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project, co-led by our group, is leveraging cloud solutions to globally standardize and analyze cancer genomics data, with the aim of uncovering commonalities and differences between molecular disease mechanisms in disparate cancer entities.

Bioinformaticians are able to help us with that understanding through analysis of large databases such as The Cancer Genome Atlas, to see if data correlates with other studies.»

Interactions are derived by re-analyzing high - and low - throughput experimental data, by mining biological databases and literature, and by genomic context analysis of 373 fully sequenced genomes.

Using deCODE's proprietary analysis tool for complex traits, the deCODE Clinical Genome Miner ™, the researchers were able to correlate a wide range of clinical, behavioral, and genotypic data, and gained important new insights into the heritability of different aspects of obesity, as well as into the complex interplay between obesity and diabetes, stroke, heart disease, and hyperlipidemia.

Three NHGRI - funded Large - Scale Genome Sequencing and Analysis Centers (LSACs) provide in - kind sequencing and data processing support:

We applied gene set enrichment analysis (GSEA)(23) to expression array data using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways.

Data generated in the lab have contributed to several international T2D consortia including the Meta - analysis of T2D in African Americans (MEDIA) Consortium that has performed meta - analysis of 17 genome - wide association studies (GWAS) for T2D in over 8,000 cases and 16,000 controls.