Sentences with phrase «omic data»

So now his lab is tracking omic data from 100 people, most of whom have elevated blood sugar levels, but have not yet been diagnosed with diabetes.

So far, collecting and integrating omic data is largely restricted to the lab — the work is still expensive and time - consuming.

Nearly a year into his experiment, though, changes in his other omic data suggested that his body was no longer using glucose properly.

What's more, the researchers hope to be able to add other types of «omics data such as RNA sequencing, epigenetic information, and histone modifications.

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.

That requires analytical and bioinformatics tools to conduct disease or therapeutic association and pathway analysis that combines various forms of «omics data.

-- In silico basic and systems biology: We develop innovative approaches to reverse engineer biological networks from omics data, model tumor progression at the genomic, transcriptomic and epigenetic level, automatically annotate new proteins and functional elements through integration of complex and heterogeneous data, including data obtained from high - throughput sequencing or time - lapse video - microscopy.

However, the interpretation of large omics data and the understanding of complex metabolic interactions in engineered microbes remains challenging.

The Application of Omics Data to the Development of AOPs — Mary T. McBride, A Systems Biology Approach to Advancing Adverse Outcome Pathways for Risk Assessment

Our laboratory has further been among the pioneers in the utilization of cloud computing to enable sharing and processing of large - scale omics data.

This tool securely integrates - omics data with clinical information, providing not only a centralised data repository but also a sophisticated and user - friendly online analysis system.

The RD - Connect Genome - Phenome Analysis Platform, developed and hosted at the CNAG - CRG, securely integrates - omics data with clinical information, providing not only a centralized data repository but also a sophisticated and user - friendly online analysis system.

As a result, a massive amount of omics data is currently being generated which will be difficult to exploit using solely bioinformatic criteria.

From their site: «OMICtools strives to accelerate research in bioinformatics, making tools accessible to everyone and offering a stimulating work environment to assist life scientists extracting new findings from the omics data.»

Routine data analyses include large scale information datasets (omics data) generated by high - throughput technologies, which address the following areas:

RD - Connect bioinformatic tools In addition, RD - Connect has developed several bioinformatic tools to help researchers analyse omics data and identify targets for potential therapies.

Over the past decades, hundreds of studies on the BXD population have created a wealth of multi-layered omics data, ranging from genomic, transcriptomic, proteomic, metabolomic, to phenomic data.

At the end of its second year, RD - Connect has successfully achieved its objectives for the period and has made significant progress on the development of the central platform for omics data and the associated bioinformatics tools for data analysis, the integration of biobanks and registries, and the ethical framework for data sharing.

Over the past decades, hundreds of studies on the BXD population have created a wealth of multi-layered omics data, ranging from genomic, transcriptomic, proteomic, metabolomic, to phenomic data (Figure 1).

Funded as part of the EU's commitment to the International Rare Diseases Research Consortium (IRDiRC), RD - Connect is a global infrastructure project that links omics data with databases, registries, biobanks, and clinical bioinformatics tools into a central research resource for rare diseases.

Set up to overcome the siloing, fragmentation and inaccessibility of datasets from different projects, it links omics data with phenotypic data and information in registries and biobanks at both an individual ‐ patient and whole ‐ cohort level to enable researchers to analyse their own data and gain a complete view of their disease and patient population of interest.

They are developing novel computational approaches that combine molecular interaction and pathway information with «omics data to develop clinically predictive models and identify therapeutically targetable pathways.

It has been set up to address the problem of fragmentation in the rare disease research field, where individual efforts often have poor interoperability and do not systematically connect data across the levels of clinical phenotype, genetics and omics data, biomaterial availability and research / trial datasets.

Waters, who is director of biological sciences at PNNL, was invited to be on the committee because of her strong expertise in microarray and omics data analysis.

My interests lie in leveraging the information hidden in large - scale omics data for better understanding of the mutational processes causing human cancer, for identifying potential cancer prevention strategies, and for developing novel approaches for targeted cancer treatment.

Not exact matches

From their analysis, which is not based on omic technologies but represents the most comprehensive compilation of GE crop composition data to date, the authors conclude that compositional differences between GE varieties and their conventional comparators are «encompassed within the natural variability of the conventional crop and that the composition of GM and conventional crops can not be disaggregated.»

The researchers developed an easy - to - use toolkit, which can be used to integrate the different layers of «omics» data from the BXD mouse population.

Using modeling and computational approaches, we will integrate high - resolution data from chromosome interactions, super-resolution images and «omics» datasets.

It should be noted that the 7th Pan Arab Human Genetics Conference will be held from 18 to 20 January 2018 at Conrad hotel in Dubai, and will discuss the Omics Era through 4 main topics: precision medicine, big data in human genetics, genomics of multifactorial disorders, and the current trend in human genetics sciences.

He is interested in elucidating mechanisms of human disease by exploring the functional effects of genetic variation through computational analysis of «- omic» sequencing data.

Our main goal in this project is to use NGS in identification of genetic causes of rare / ultrarare early - onset neurologic diseases, integrating «omics» platforms with systematic approaches to enrich and redefine phenotypic ontology in these conditions, allowing a comprehensive analysis of genomic data.

To help researchers study rare diseases, RD - Connect links different data types - omics (e.g. genomics), clinical information, patient registries and biobanks - into a common resource.

288/5: 45 Integration of functional «omics» data uncovers mitochondrial deficiency in Smith - Magenis syndrome.

Additional «- omics» data streams include: transcriptomics, the pattern of RNA synthesis from DNA; proteomics, the distribution of proteins in cells; interactomics, the patterns of protein - protein and protein — nucleic acid interactions; and metabolomics, the nature and traffic patterns of transformations of small molecules by the biochemical pathways active in cells.

The GeneLab project houses spaceflight and spaceflight relevant multi-omics data in a publicly accessible data commons, and collaborates with NASA - funded principal investigators to enable omics analyses on their experiments.

He is co-founder of MD Omics, a company that analyzes complex data sets to enable more precise clinical care, as well as a nonprofit organization that helps youths make healthier choices for their bodies and their communities.

He is co-founder of MD Omics, a company that analyzes complex data sets to enable more precise clinical care, as well as