AIMC Topic: Escherichia coli

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Deep learning and single-cell phenotyping for rapid antimicrobial susceptibility detection in Escherichia coli.

Communications biology
The rise of antimicrobial resistance (AMR) is one of the greatest public health challenges, already causing up to 1.2 million deaths annually and rising. Current culture-based turnaround times for bacterial identification in clinical samples and anti...

Functional annotation of enzyme-encoding genes using deep learning with transformer layers.

Nature communications
Functional annotation of open reading frames in microbial genomes remains substantially incomplete. Enzymes constitute the most prevalent functional gene class in microbial genomes and can be described by their specific catalytic functions using the ...

Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision.

Science advances
Owing to the nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, ar...

Methyl cellulose/okra mucilage composite films, functionalized with Hypericum perforatum oil and gentamicin, as a potential wound dressing.

International journal of biological macromolecules
There is a growing demand for the development of functional wound dressings enriched with bioactive natural compounds to improve the quality of life of the population by accelerating the healing process of chronic wounds. In this regard, a functional...

Design, Evaluation, and Implementation of Synthetic Isopentyldiol Pathways in .

ACS synthetic biology
Isopentyldiol (IPDO) is an important raw material in the cosmetic industry. So far, IPDO is exclusively produced through chemical synthesis. Growing interest in natural personal care products has inspired the quest to develop a biobased process. We p...

DensePPI: A Novel Image-Based Deep Learning Method for Prediction of Protein-Protein Interactions.

IEEE transactions on nanobioscience
Protein-protein interactions (PPI) are crucial for understanding the behaviour of living organisms and identifying disease associations. This paper proposes DensePPI, a novel deep convolution strategy applied to the 2D image map generated from the in...

TidyTron: Reducing lab waste using validated wash-and-reuse protocols for common plasticware in Opentrons OT-2 lab robots.

SLAS technology
Every year biotechnology labs generate a combined total of ∼5.5 million tons of plastic waste. As the global bioeconomy expands, biofoundries will inevitably increase plastic consumption in-step with synthetic biology scaling. Decontamination and reu...

A deep learning method for predicting the minimum inhibitory concentration of antimicrobial peptides against using Multi-Branch-CNN and Attention.

mSystems
Antimicrobial peptides (AMPs) are a promising alternative to antibiotics to combat drug resistance in pathogenic bacteria. However, the development of AMPs with high potency and specificity remains a challenge, and new tools to evaluate antimicrobial...

Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data.

Journal of mathematical biology
We propose a machine learning framework for the data-driven discovery of macroscopic chemotactic Partial Differential Equations (PDEs)-and the closures that lead to them- from high-fidelity, individual-based stochastic simulations of Escherichia coli...

Nitric oxide releasing polyvinyl alcohol and sodium alginate hydrogels as antibacterial and conductive strain sensors.

International journal of biological macromolecules
Conductive hydrogels have promising applications in flexible electronic devices and artificial intelligence, which have attracted much attention in recent years. However, most conductive hydrogels have no antimicrobial activity, inevitably leading to...