CD Biosynsis is dedicated to providing high-quality AI and machine learning services for the "learn" phase of synthetic biology, aiming to help researchers around the world advance their cutting-edge research. We have the ability and extensive experience to help bring diverse synthetic biology applications and creative ideas to fruition.
Introduction to AI and Machine Learning
Artificial Intelligence (AI) stands as a realm within computer science, dedicated to the creation of systems proficient in executing tasks inherently demanding human-like intelligence. Such undertakings encompass quandary resolution, decision formulation, apprehension of natural language nuances, identification of motifs, and assimilation of erudition through experience.
Machine Learning (ML), nestled as a subdivision of AI, revolves around the evolution of algorithms and frameworks conducive to facilitating computers in imbibing insights and making prognostications or determinations rooted in data substrata. Instead of explicit programming dictating task fulfillment, machine learning frameworks discern patterns and correlations inherent within data repositories, thereby facilitating precise prognostications or determinations within novel, uncharted scenarios.
In the field of synthetic biology, the "learn" phase involves gaining a deep understanding of biological systems and their components to inform the design and engineering of novel biological constructs. AI and machine learning emerge as a potent tool for catalyzing a paradigm shift in researchers' approaches to this phase. These technologies empower the extraction of invaluable discernments from intricate biological data arrays, anticipation of outcomes, and streamlining of experimental methodologies.
Fig 1. Relationship diagram between AI, ML and DL. (Sevakula R K, et al., 2020)
Service Offering
Through AI and machine learning services, CD Biosynsis can help our clients enhance research capabilities, make data-driven decisions, and accelerate scientific discoveries. Browse our services below or use our online inquiry form for more information.
Optimized Strain Design & Engineering
Deconstruct intricate genetic and metabolic pathways, predict optimal genetic modifications and proliferation conditions, and propose optimal strain designs for improved protein production, biofuel synthesis, or pharmaceutical production.
Predictive Modeling for Protein
Analyze protein databases to foretell how specific mutations will impact protein functionality and design innovative proteins with desired properties, such as enhanced binding affinity or enzymatic activity.
Drug Discovery and Development
Accelerate drug discovery by identifying potential drug candidates, predicting their interactions and optimizing their properties.
Bioprocess Optimization
Optimize fermentation and bioprocessing conditions to reduce process costs and achieve maximum yield and efficiency.
Data Analysis and Integration
Integrate and analyze various datasets, such as genomics, proteomics and metabolomics data to uncover hidden patterns and insights.
Personalized Medicine and Biomarker Discovery
Identify biomarkers for disease diagnosis, prognosis, and prediction of treatment response, thereby contributing to the development of personalized treatment strategies for precision medicine.
How Can We Help?
Reduced Research Costs and Time
Help our clients speed up the research process, reduce experimental iterations and optimize resource allocation.
Innovation and Competitive Edge
Provide cutting-edge artificial intelligence and machine learning services to make your company stand out in your industry.
Customized Solutions
Tailored to the specific needs of each client, providing customized solutions that align with their research goals.
CD Biosynsis helps our clients enhance their research capabilities, make data-driven decisions, and accelerate scientific discovery by integrating artificial intelligence and machine learning services into our synthetic biology platform.
Reference
- Sevakula, R K.; et al. State-of-the-Art Machine Learning Techniques Aiming to Improve Patient Outcomes Pertaining to the Cardiovascular System. Journal of the American Heart Association, 2020, 9(4).
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