Visualising Complex Data Results from 100,000 Cancer Patients
News Dec 12, 2012
Earlier this week it was announced that up to 100,000 patients with cancer and rare diseases in England will have their entire genetic code sequenced, with the UK Prime Minister outlining that £100m has been set aside for the project over the next three to five years.
This is welcome news as for decades, biomedical scientists have been looking for new ways to diagnose cancers at an early, curable stage and also to select the optimal therapy for individual patients. At the moment, cancer treatments are effective in only some of the patients undergoing therapy, and many cancer patients are still being diagnosed too late, once the cancer is already too far advanced. Despite these challenges, researchers are now exploring how unique biomarkers could help to improve the outcome for people with cancer by enhancing detection and treatment approaches.
However as with the 100,000 sample announced, mapping this kind of genetic data and performing genome sequencing in an attempt to try and personalise medical diagnosis and care, leads to enormous amounts of data being produced in order to classify patients into groups e.g. by distinctive biomarkers.
In addition, once you get to the clinical stage by taking DNA or blood samples even more data is produced and needed to be understand before patients can be grouped. Fortunately, in recent years there have been major developments in analysis software that can handle DNA mapping on this scale, helping to structure patients into groups and identifying which biomarkers should be used.
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.
Synthetic DNA Shuffling Enzyme Outpaces Natural CounterpartNews
A new synthetic enzyme, crafted from DNA rather than protein, flips lipid molecules within the cell membrane, triggering a signal pathway that could be harnessed to induce cell death in cancer cells. Researchers say their lipid-scrambling DNA enzyme is the first in its class to outperform naturally occurring enzymes – and does so by three orders of magnitudeREAD MORE
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.