Biotechnological, Genomics and Systems–Synthetic Biology Revolution: Redesigning Genetic Code for a Pagmatic Systems Medicine
News Mar 21, 2012
Powerful modern technologies, including next-generation sequencing (NGS) and mass spectroscopy (MS), allow for rapid developments in systems biology and syn¬thetic biology. These advances allow for an unprecedented approach for genomics, transcriptomics, epigenomics and proteomics, providing deeper insights into the interactions of genes, proteins and small molecules. Understanding how interact¬ing biological systems regulate functional networks, chromatin, gene expression, signaling pathways and crucial cellular processes is essential for the future of systems medicine. Although these innovative developments are considered pragmatic and funded by governments and industry, here the author discusses the latest advances and challenges in ‘rewiring’ cellular signaling circuits, and redesign¬ing and editing genetic code for a systems medicine-based pragmatic revolution in health.
This article was published online in Expert Review of Medical Devices and is free to access.
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.