Qiagen Bids $100M to Acquire Exiqon
News Mar 31, 2016
QIAGEN has announced that it has decided to submit a conditional voluntary takeover offer to the shareholders of Exiqon A/S (NASDAQ OMX Copenhagen: EXQ) to purchase all shares in Exiqon. The acquisition is expected to expand QIAGEN’s leadership position in Sample to Insight solutions for RNA analysis. This announcement is made in accordance with section 4 of the Danish Executive Order no. 562 of 2 June 2014 on takeover bids ("Executive Order on Takeover Bids").
Exiqon, founded in 1995 and headquartered in Vedbaek, Denmark, is a leader in the emerging market for non-coding RNA (ncRNA) such as micro RNA (miRNA) and long non-coding RNA (lncRNA). These functionally important molecules are demonstrating great promise in cellular function and regulation. In addition to products spanning sample technologies, assay technologies and bioinformatics solutions, Exiqon brings to QIAGEN a portfolio of proprietary technologies and know-how used in molecular testing, including relevant Locked Nucleic Acid (LNA) technology. LNA greatly improves the specificity and sensitivity in PCR, NGS target enrichment and in functional assays. The company has around 100 employees at sites in Denmark and the US and reported net sales of approximately $20 million in 2015.
Algorithm Speeds Up Medical Image Analysis 1000 TimesNews
Medical image registration is a common technique that involves overlaying two images, such as magnetic resonance imaging (MRI) scans, to compare and analyze anatomical differences in great detail. Researchers have described a machine-learning algorithm that can register brain scans and other 3-D images more than 1,000 times more quickly using novel learning techniques.
Mechanism Controlling Multiple Sclerosis Risk IdentifiedNews
Researchers at Karolinska Institutet have now discovered a new mechanism of a major risk gene for multiple sclerosis (MS) that triggers disease through so-called epigenetic regulation. They also found a protective genetic variant that reduces the risk for MS through the same mechanism.
Antarctic Worm and Machine Learning Help Identify Cerebral Palsy EarlierNews
A research team has released a study in the peer-reviewed journal BMC Bioinformatics showing that DNA methylation patterns in circulating blood cells can be used to help identify spastic cerebral palsy (CP) patients. The technique which makes use of machine learning, data science and even analysis of Antarctic worms, raises hopes for earlier targeted CP therapies.