AI Medical Compendium Journal:
Current opinion in biotechnology

Showing 11 to 20 of 26 articles

Deep learning in regulatory genomics: from identification to design.

Current opinion in biotechnology
Genomics and deep learning are a natural match since both are data-driven fields. Regulatory genomics refers to functional noncoding DNA regulating gene expression. In recent years, deep learning applications on regulatory genomics have achieved rema...

Perspectives for self-driving labs in synthetic biology.

Current opinion in biotechnology
Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is pr...

Machine learning for predicting phenotype from genotype and environment.

Current opinion in biotechnology
Predicting phenotype with genomic and environmental information is critically needed and challenging. Machine learning methods have emerged as powerful tools to make accurate predictions from large and complex biological data. Here, we review the pro...

Continuous biomanufacturing with microbes - upstream progresses and challenges.

Current opinion in biotechnology
Current biomanufacturing facilities are mainly built for batch or fed-batch operations, which are subject to low productivities and do not achieve the great bioconversion potential of the rewired cells generated via modern biotechnology. Continuous b...

The future of Artificial Intelligence for the BioTech Big Data landscape.

Current opinion in biotechnology
Recent Industry 4.0 advancements are making available massive amounts of data for the development of innovative BioTech solutions. However, several challenges need to be overcome to correctly use data and novel, non-pharma technologies to greatly spe...

Machine learning to navigate fitness landscapes for protein engineering.

Current opinion in biotechnology
Machine learning (ML) is revolutionizing our ability to understand and predict the complex relationships between protein sequence, structure, and function. Predictive sequence-function models are enabling protein engineers to efficiently search the s...

Artificial intelligence: a solution to involution of design-build-test-learn cycle.

Current opinion in biotechnology
Iterative design-build-test-learn (DBTL) cycles are routinely performed during microbial strain development. This useful approach integrates computational strain design, genetic engineering, fermentation testing, and omics analysis to reveal and reso...

Neural interface systems with on-device computing: machine learning and neuromorphic architectures.

Current opinion in biotechnology
Development of neural interface and brain-machine interface (BMI) systems enables the treatment of neurological disorders including cognitive, sensory, and motor dysfunctions. While neural interfaces have steadily decreased in form factor, recent dev...

Applications of artificial intelligence to enzyme and pathway design for metabolic engineering.

Current opinion in biotechnology
Metabolic engineering for developing industrial strains capable of overproducing bioproducts requires good understanding of cellular metabolism, including metabolic reactions and enzymes. However, metabolic pathways and enzymes involved are still unk...

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems.

Current opinion in biotechnology
Modern agriculture and food production systems are facing increasing pressures from climate change, land and water availability, and, more recently, a pandemic. These factors are threatening the environmental and economic sustainability of current an...