Software/Web-Based AI/ML Tools
JFAB’s AI and machine learning tools guide biomanufacturing research and enable powerful analysis and predictions.
Automated Recommendation Tool
Guiding strain optimization and experiment design
The processes that take place in synthetic biology are unpredictable, leading scientists to take time-consuming approaches to figure out what works. Making synthetic biology more predictable would accelerate progress.
The Automated Recommendation Tool (ART) suite leverages machine learning to guide synthetic biology in a systematic fashion, providing actionable recommendations that accelerate timelines.
ART has been successfully used to optimize media, design pathways, and engineer host organisms — advances that have led to improved production of key bioproducts.
PISCES
Structuring bioprocess data for knowledge extraction and analysis
Decades of bioprocess engineering data are trapped in unstructured formats like PDFs and images, making it almost impossible to systematically analyze or leverage this data for modern AI applications.
PISCES takes in bioprocess datasets from diverse sources and harmonizes them into a unified, machine-readable format that computational models can leverage for analysis and automated design.
BioPKS Pipeline & TridentSynth
Pathway design for complex, high-value chemicals
Identifying biosynthetic pathways can be a time-consuming process relying on manual literature searches. Existing methods are confined to a limited chemical space, making it difficult to access complex products like fuels and plastic polymers.
The BioPKS Pipeline predicts and designs novel biosynthetic pathways for producing complex, high-value chemicals that are otherwise largely inaccessible. TridentSynth makes this powerful capability accessible to all through a user-friendly web-based platform.
Advanced computational tools guide experiments, analyze data, and provide impactful insights, speeding up the path to discovery.