AIMC Topic: Synthetic Biology
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A nonlinear neural network based on an analog DNA toehold mediated strand displacement reaction circuit.
Nanoscale
May 5, 2022
The DNA toehold mediated strand displacement reaction is one of the semi-synthetic biology technologies for next-generation computers. In this article, we present a framework for a novel nonlinear neural network based on an engineered biochemical cir...
Microbial chassis engineering drives heterologous production of complex secondary metabolites.
Biotechnology advances
Apr 26, 2022
The cryptic secondary metabolite biosynthetic gene clusters (BGCs) far outnumber currently known secondary metabolites. Heterologous production of secondary metabolite BGCs in suitable chassis facilitates yield improvement and discovery of new-to-nat...
Promoter prediction in nannochloropsis based on densely connected convolutional neural networks.
Methods (San Diego, Calif.)
Mar 31, 2022
Promoter is a key DNA element located near the transcription start site, which regulates gene transcription by binding RNA polymerase. Thus, the identification of promoters is an important research field in synthetic biology. Nannochloropsis is an im...
Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity.
Nature communications
Jan 27, 2022
Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning t...
Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network.
Bio Systems
Jan 19, 2022
In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibility of programming cells or unicellular organisms in order to enable them to perform certain tasks, wh...
Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.
Computational and mathematical methods in medicine
Dec 13, 2021
Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach...
Cheetah: A Computational Toolkit for Cybergenetic Control.
ACS synthetic biology
Apr 27, 2021
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups ...
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...
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....
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 ...
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