AIMC Topic: Synthetic Biology

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Unsupervised manifold learning of collective behavior.

PLoS computational biology Feb 12, 2021
Collective behavior is an emergent property of numerous complex systems, from financial markets to cancer cells to predator-prey ecological systems. Characterizing modes of collective behavior is often done through human observation, training generat...
Unsupervised Machine Learning Models, Biological Fishes Ecosystem Computational Biology Systems Biology Humans Animals Behavior Social Behavior Systems Analysis Synthetic Biology Behavior, Animal Models, Psychological
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Sequence-to-function deep learning frameworks for engineered riboregulators.

Nature communications Oct 7, 2020
While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules....
Synthetic Biology Base Sequence Genome, Human Structure-Activity Relationship Natural Language Processing Datasets as Topic Genetic Engineering Riboswitch Genome, Viral Mutagenesis Biotechnology Humans Computer Simulation Deep Learning Models, Genetic
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A deep learning approach to programmable RNA switches.

Nature communications Oct 7, 2020
Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced ...
Humans Genome, Viral Thermodynamics Genetic Engineering Riboswitch Kinetics Deep Learning Datasets as Topic Transcription Factors Synthetic Biology
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A machine learning Automated Recommendation Tool for synthetic biology.

Nature communications Sep 25, 2020
Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long develop...
Beer Dodecanol Biofuels Saccharomyces cerevisiae Metabolic Engineering Fatty Acids Synthetic Biology Machine Learning Escherichia coli Bayes Theorem
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Sequencing enabling design and learning in synthetic biology.

Current opinion in chemical biology Aug 6, 2020
The ability to read and quantify nucleic acids such as DNA and RNA using sequencing technologies has revolutionized our understanding of life. With the emergence of synthetic biology, these tools are now being put to work in new ways - enabling de no...
Machine Learning Synthetic Biology Base Sequence
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Bio-informational futures: The convergence of artificial intelligence and synthetic biology.

EMBO reports Feb 11, 2020
Synthetic biology and artificial intelligence naturally converge in the biofoundry. Navigating the ethical and societal issues of the biofoundry's potential remains a major challenge.
Artificial Intelligence Forecasting Synthetic Biology
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Reinforcement Learning for Bioretrosynthesis.

ACS synthetic biology Dec 30, 2019
Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process is still long and costly, and efficient computational design tools are requi...
Algorithms Metabolic Networks and Pathways Models, Biological Markov Chains Synthetic Biology Monte Carlo Method Artificial Intelligence Software Reinforcement, Psychology Enzymes Metabolic Engineering
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Function2Form Bridge-Toward synthetic protein holistic performance prediction.

Proteins Oct 29, 2019
Protein engineering and synthetic biology stand to benefit immensely from recent advances in silico tools for structural and functional analyses of proteins. In the context of designing novel proteins, current in silico tools inform the user on indiv...
Humans Coagulase Structure-Activity Relationship Mucin-1 Antibodies Protein Engineering Synthetic Biology Machine Learning Staphylococcus aureus Models, Statistical
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A Comprehensive Network Atlas Reveals That Turing Patterns Are Common but Not Robust.

Cell systems Sep 18, 2019
Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to dis...
Morphogenesis Humans Body Patterning Atlases as Topic Animals Neural Networks, Computer Computer Heuristics Models, Biological Synthetic Biology
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Dynamic Metabolomics for Engineering Biology: Accelerating Learning Cycles for Bioproduction.

Trends in biotechnology Aug 28, 2019
Metabolomics is a powerful tool to rationally guide the metabolic engineering of synthetic bioproduction pathways. Current reports indicate great potential to further develop metabolomics-directed synthetic bioproduction. Advanced mass metabolomics m...
Bioengineering Metabolomics Machine Learning Metabolic Networks and Pathways Mass Spectrometry Synthetic Biology
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