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Welcome to CD ComputaBio, your premier partner in leveraging cutting-edge artificial intelligence solutions in the field of synthetic biology. Our team of experts is dedicated to revolutionizing how research and development processes are conducted, enhancing efficiency, precision, and innovation in the realm of biological engineering. Through our advanced AI technologies and expertise, we offer a range of services tailored to meet the unique needs of our clients in the rapidly evolving landscape of synthetic biology.

Synthetic Biology Engineering Design Principles

Synthetic biologists employ engineering design principles and the predictability of engineering to control complex biological systems.

  • Design - A hypothesis that a DNA sequence or set of cellular operations can achieve a desired design goal.
  • Build - Implementing the design steps on a biological system. Mainly involves the synthesis of DNA fragments and their formation.
  • Test - Generate data to examine and measure the extent to which a phenotype achieves its intended goals, and evaluate any off-target or unforeseen side effects.
  • Learning - Using test data, learning is more effective than random search in driving loops to expectations.

Fig 1. Linear classification with a biological student–teacher network.Fig 1. Linear classification with a biological student–teacher network. (Nesbeth D N, et al., 2016)

Our Services

  • Cell Engineering

Our AI technology enables the design and automation of high-throughput cell-based assays for drug screening, toxicity testing, and functional analysis. By integrating AI-powered image analysis and data interpretation capabilities, we accelerate the discovery of novel therapeutics and biomarkers.

  • Bioinformatics Processing

Using state-of-the-art machine learning techniques, our platform can process large-scale datasets, perform sequence analysis, identify genetic variations, and predict molecular structures and functions. At CD ComputaBio our bioinformatics processing service can provide valuable insights to support your scientific endeavors.

  • Biological Sensor Development

Our AI-based biological sensor development service aims to enhance the accuracy, sensitivity, and efficiency of sensors used to detect biological entities or processes. By leveraging the power of AI, we can optimize the design and functionality of biological sensors to enable real-time monitoring, data analysis, and quick decision-making.

Our Capabilities

Gene Sequence Design

Our AI algorithms can predict and optimize gene sequences for specific functions, such as protein expression, enzyme activity, or metabolic pathway efficiency. This capability streamlines the process of genetic engineering and accelerates the development of novel biological constructs.

Metabolic Pathway Engineering

We specialize in designing and optimizing metabolic pathways for enhanced production of valuable compounds, such as biofuels, pharmaceuticals, and specialty chemicals. Our AI models can predict optimal pathway configurations and guide experimental efforts for maximum productivity.

Protein Structure Prediction

Using advanced deep learning techniques, we can accurately predict protein structures and functions based on amino acid sequences. This capability is invaluable for drug discovery, enzyme engineering, and protein design applications.

Bioprocess Optimization

Our AI solutions can optimize bioprocess parameters, such as fermentation conditions, nutrient supplementation, and culture media composition. By fine-tuning these parameters, we maximize product yields, reduce production costs, and improve process efficiency.

At CD ComputaBio, we leverage state-of-the-art AI algorithms, machine learning techniques, and data-driven approaches to empower scientists and engineers in their quest to create novel biological solutions. Our AI solutions are tailored to meet the evolving needs of the synthetic biology community, providing valuable insights, predictive modeling, and optimization strategies for diverse applications. If you are interested in our solutions or have any questions, please feel free to contact us.

Reference:

  • >Nesbeth D N, Zaikin A, Saka Y, et al. Synthetic biology routes to bio-artificial intelligence[J]. Essays in biochemistry, 2016, 60(4): 381-391.

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