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Escherichia coli

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Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control.

SLAS technology
During process development, the experimental search space is defined by the number of experiments that can be performed in specific time frames but also by its sophistication (e.g., inputs, sensors, sampling frequency, analytics). High-throughput liq...

Machine learning modelling for the ultrasonication-mediated disruption of recombinant E. coli for the efficient release of nitrilase.

Ultrasonics
The ultrasonication-mediated cell disruption of recombinant E. coli was modeled using three machine learning techniques namely Multiple linear regression (MLR), Multi-layer perceptron (MLP) and Sequential minimal optimization (SMO). The four attribut...

Detection of DNA base modifications by deep recurrent neural network on Oxford Nanopore sequencing data.

Nature communications
DNA base modifications, such as C5-methylcytosine (5mC) and N6-methyldeoxyadenosine (6mA), are important types of epigenetic regulations. Short-read bisulfite sequencing and long-read PacBio sequencing have inherent limitations to detect DNA modifica...

Lessons from Two Design-Build-Test-Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning.

ACS synthetic biology
The Design-Build-Test-Learn (DBTL) cycle, facilitated by exponentially improving capabilities in synthetic biology, is an increasingly adopted metabolic engineering framework that represents a more systematic and efficient approach to strain developm...

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms.

Journal of biophotonics
Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of cli...

Synthesis, characterization, antimicrobial and antimetastatic activity of silver nanoparticles synthesized from Ficus ingens leaf.

Artificial cells, nanomedicine, and biotechnology
Cancer incidence is still increasing due to inadequate responsive treatments. Inertness and biocompatibility of nanoparticles synthesized using plant extracts have shown therapeutic applications and make it to be a good anti-cancer candidates. This s...

Metabarcoding and machine learning analysis of environmental DNA in ballast water arriving to hub ports.

Environment international
While ballast water has long been linked to the global transport of invasive species, little is known about its microbiome. Herein, we used 16S rRNA gene sequencing and metabarcoding to perform the most comprehensive microbiological survey of ballast...

Machine learning framework for assessment of microbial factory performance.

PloS one
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other han...

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli.

ACS synthetic biology
The field of synthetic biology aims to make the design of biological systems predictable, shrinking the huge design space to practical numbers for testing. When designing microbial cell factories, most optimization efforts have focused on enzyme and ...

Synthesis of Ag/AgCl modified anhydrous basic bismuth nitrate from BiOCl and the antibacterial activity.

Materials science & engineering. C, Materials for biological applications
Novel nanocomposite of Ag/AgCl and a single phase of anhydrous basic bismuth nitrate (ABBN)-BiO(OH)(NO) with efficient antibacterial activity was prepared from BiOCl. Microstructure was characterized as AgCl nanotubes and Ag nanoparticles mixed with ...