AIMC Topic: Escherichia coli

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Synthesis and biological characterization of MnZnEuDyFeO nanoparticles by sonochemical approach.

Materials science & engineering. C, Materials for biological applications
Metallic nanoparticles (NPs) possess unique properties which makes them attractive candidates for various applications especially in field of experimental medicine and drug delivery. Many approaches were developed to synthesize divers and customized ...

Massive computational acceleration by using neural networks to emulate mechanism-based biological models.

Nature communications
For many biological applications, exploration of the massive parametric space of a mechanism-based model can impose a prohibitive computational demand. To overcome this limitation, we present a framework to improve computational efficiency by orders ...

Use of high-content analysis and machine learning to characterize complex microbial samples via morphological analysis.

PloS one
High Content Analysis (HCA) has become a cornerstone of cellular analysis within the drug discovery industry. To expand the capabilities of HCA, we have applied the same analysis methods, validated in numerous mammalian cell models, to microbiology m...

Emergence of mcr-1 mediated colistin resistant Escherichia coli from a hospitalized patient in Bangladesh.

Journal of infection in developing countries
INTRODUCTION: The emergence of plasmid mediated mcr in bacteria has become global public health threat. Herein, we report a mcr-1 positive E. coli in normal human flora from a patient admitted in Dhaka Medical College Hospital (DMCH).

Metabolic perceptrons for neural computing in biological systems.

Nature communications
Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing usi...

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...