Celera accelerates genetic marker research with IDBS, helping to identify coronary heart disease biomarkers. IDBS’ translational research informatics platform provides flexible, workflow driven integration, analysis and visualization, accelerating the scientific understanding of biomarker data.
- Celera had a goal: to be able to integrate and utilize other research data
- IDBS worked with its team to produce workflows to integrate, analyze, and visualize both internal and publicly-available biomarker data
- E-WorkBook connected the dots, streamlining research
Having identified interesting single nucleotide polymorphisms (SNPs) in initial studies, Celera successfully carried out additional large studies to further validate disease associations and develop biomarker tests.
Beyond validation, scientists inquire whether there are other SNPs in the same region (or SNP combinations) that are more strongly associated with the disease indication and inquire about the functional nature of the gene variants.
Scientists need information from many diverse quantitative, qualitative, web based and textual data sources to address these questions, which creates a complex data integration challenge.
When researchers rely solely on statistical analysis, critical gene variants can be missed, thereby subverting subsequent literature mining and biological annotation and significantly delaying translational research.
IDBS and Celera have constructed workflows to integrate, analyze and visualize both publicly available and internal biomarker data, including nucleotide and protein sequence-based phylogenetic trees, transcriptional and proteomic tissue profiles, common promoter motifs, co-regulated gene expression, GO ontologies and interaction networks.
IDBS workflows automatically annotate putative genetic markers from public data sources and third party products.
Celera is using and adapting several workflows from the IDBS CustomerHub, thus benefiting from the community’s experience while reducing development times.
Researchers interact with data using intuitive and interactive visualization tools.
IDBS workflows provided rapid and thorough initial insights into the functional relevance (both molecular consequence of variant and possible biological processes involved) to the clinical phenotype(s).
IDBS facilitates the critical follow up studies of a gene variant, for example, the Kinesin protein family (KIF6) associated with increased risk of coronary heart disease, as well as statin response.
IDBS workflows prioritized literature queries from available data and informed follow up studies, thus ensuring that certain gene variants were further investigated, which made significant contribution to the ongoing understanding and treatment of disease.