AIMC Topic: Escherichia coli

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Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

Microbiology spectrum
UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human...

Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality.

NPJ systems biology and applications
Genome-scale metabolic models are powerful tools for understanding cellular physiology. Flux balance analysis (FBA), in particular, is an optimization-based approach widely employed for predicting metabolic phenotypes. In model microbes such as Esche...

Context-dependent design of induced-fit enzymes using deep learning generates well-expressed, thermally stable and active enzymes.

Proceedings of the National Academy of Sciences of the United States of America
The potential of engineered enzymes in industrial applications is often limited by their expression levels, thermal stability, and catalytic diversity. De novo enzyme design faces challenges due to the complexity of enzymatic catalysis. An alternativ...

NIR spectroscopy-CNN-enabled chemometrics for multianalyte monitoring in microbial fermentation.

Biotechnology and bioengineering
As the biopharmaceutical industry looks to implement Industry 4.0, the need for rapid and robust analytical characterization of analytes has become a pressing priority. Spectroscopic tools, like near-infrared (NIR) spectroscopy, are finding increasin...

Combined substituent number utilized machine learning for the development of antimicrobial agent.

Scientific reports
The utilization of machine learning has a potential to improve the environment of the development of antimicrobial agents. For practical use of machine learning, it is important that the conversion of molecules information to an appropriate descripto...

MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

BMC bioinformatics
BACKGROUND: The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This i...

Optimization of medium components for protein production by Escherichia coli with a high-throughput pipeline that uses a deep neural network.

Journal of bioscience and bioengineering
To optimize rapidly the medium for green fluorescent protein expression by Escherichia coli with an introduced plasmid, pRSET/emGFP, a single-cycle optimization pipeline was applied. The pipeline included a deep neural network (DNN) and mathematical ...

Genetic algorithm-based semisupervised convolutional neural network for real-time monitoring of Escherichia coli fermentation of recombinant protein production using a Raman sensor.

Biotechnology and bioengineering
As a non-destructive sensing technique, Raman spectroscopy is often combined with regression models for real-time detection of key components in microbial cultivation processes. However, achieving accurate model predictions often requires a large amo...

AI and Knowledge-Based Method for Rational Design of Sigma70 Promoters.

ACS synthetic biology
Expanding sigma70 promoter libraries can support the engineering of metabolic pathways and enhance recombinant protein expression. Herein, we developed an artificial intelligence (AI) and knowledge-based method for the rational design of sigma70 prom...

Pregnancy-associated asymptomatic bacteriuria and antibiotic resistance in the Maternity and Children's Hospital, Arar, Saudi Arabia.

Journal of infection in developing countries
INTRODUCTION: The Ministry of Health in Saudi Arabia provides comprehensive antenatal care for all pregnant women with all required investigations. However, it does not include urine culture for diagnosis of asymptomatic bacteriuria (ASB). This is th...