For over half a decade, the Centre for Bioenergy Innovation (CBI) has been tinkering with plant and microbial genes to address the ultimate challenge of a sustainable, bio-based economy.
The CBI uses supercomputers, deep learning algorithms and gene editing tools such as CRISPR Cas9 to link genotype to phenotype. However, their research has been plagued by the incompatibility of existing gene-splicing models with microbial genomes.
To improve the design of CRISPR Cas9 machinery, scientists at Oak Ridge National Library (ORNL) built an explainable AI model and trained it to identify the molecular cues that enable targeting of specific regions of a microbial genome. The new model, called an iterative random forest, has already been shown to optimize the cleavage and binding of DNA into E. Coli bacteria.
Profound Implications
Converging artificial intelligence and quantum biology in this way has profound implications for the work of the CBI. As the AI model improves, the researchers will be able to enhance processes like bacterial fermentation and feedstock mechanisms, thus contributing to the development of a sustainable bioeconomy.
The project was funded jointly by the Department of Energy's Genomic Science Program, the CBI, the ORNL research program and the Oak Ridge Leadership Computing Facility.
Are you a techie who knows how to write? Then join our Team! Wanted:
- News Writer (Romania based)
Details here