Artificial Intelligence and genetics are some of the most complex research fields ever created. AI and genomic research specialists have recently joined hands in an attempt to improve the efficiency and accuracy of the CRISPR gene-editing technology.
CRISPR is a nano-technology that cuts and alters DNA at a specific point in a specific gene and is used from agriculture to healthcare.
AI predicts gene altering effects
The result of the collaboration work between AI specialists and genetics researchers is called Elevation. This new tool relies on machine learning to predict off-target unexpected effects of gene editing using the CRISPR system.
Oftentimes, genomic regions are similar, so editing the right gene is a challenging task. Altering the wrong gene can result in disastrous unintended consequences, ruining years of work and advanced research.
Of course, researchers want to reduce the probability of such accidents. Using computational tools such as Elevation, they can input the name of the gene they want to modify and the AI search engine then returns a list of guides predicting on-target or off-target effects.
Here is how Microsoft describes this process:
Elevation provides researchers with two kinds of off-target scores for every guide: individual scores for one target region and a single overall summary score for that guide.
Target scores are machine-learning based probabilities provided for every single region on the genome that something bad could happen. For every guide, Elevation returns hundreds to thousands of these off-target scores.
For researchers trying to determine which of potentially hundreds of guides to use for a given experiment, these individual off-target scores alone can be cumbersome, noted Listgarten.
The summary score is a single number that lumps the off-target scores together to provide an overview of how likely the guide is to disrupt the cell over all its potential off-targets.
For more information, you can check out the video below:
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