Agilent Names CNAG as Certified Provider of Target-Enrichment Services
News Feb 23, 2015
Agilent Technologies Inc. today announced that it has named the Centro Nacional de Análisis Genómico (CNAG) in Barcelona—one of Europe’s leading genome analysis centers—as an Agilent Certified Service Provider for target enrichment.
Agilent certifies select laboratories that leverage the company’s market-leading technologies to provide analysis services of the highest quality. With an Agilent Certified Service Provider, customers get reliable results from a lab that has been certified to provide target enrichment services, without the cost or technical challenges of implementing next-generation sequencing technology in their own lab.
“We are pleased to have CNAG as a certified member of our service provider program,” said Jean-Claude Gerard, Agilent’s senior sales director for Europe, the Middle East, Africa and India. “The center is known for its vital collaborations with scientists on a wide range of research projects, particularly projects involving rare diseases of genetic origin.”
In connection with the certification, Agilent will sponsor the CNAG Symposium on Genome Research: Rare Diseases in Barcelona on Feb. 26. The free symposium is a joint effort between CNAG and Agilent to promote the use of exome sequencing in research projects.
“In recent years, whole exome sequencing technologies have proved to be powerful and cost-effective means of identifying genetic variants underlying rare disorders,” said CNAG director Ivo G. Gut. “Here at the CNAG, we perform exome sequencing with Agilent’s market-leading products.”
More than 30 million Europeans are affected by 7,000 rare diseases, most of which have no effective treatment. Symptoms are usually chronic, degenerative and life-threatening. In fact, 30 percent of patients die before their fifth birthday. Most of these diseases have a genetic origin and are caused by mutations in protein-coding regions.
Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have been studied using single cell RNA-sequencing (scRNA-seq). This finding could help researchers identify new cell subtypes and differentiate between healthy and diseased cells.