AIMC Topic: Escherichia coli

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Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning.

Nature medicine
Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based t...

Main-Chain Sulfonium-Containing Homopolymers with Negligible Hemolytic Toxicity for Eradication of Bacterial and Fungal Biofilms.

ACS macro letters
Antimicrobials against planktonic cells and established biofilms at low doses are in increasing demand to tackle antibiotic-resistant biofilm infections. As a promising alternative to antibiotics, cationic polymers can effectively kill planktonic mic...

Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

International journal of molecular sciences
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...

Robotic end-to-end fusion of microtubules powered by kinesin.

Science robotics
The active assembly of molecules by nanorobots has advanced greatly since “molecular manufacturing”—that is, the use of nanoscale tools to build molecular structures—was proposed. In contrast to a catalyst, which accelerates a reaction by smoothing t...

A Graph Feature Auto-Encoder for the prediction of unobserved node features on biological networks.

BMC bioinformatics
BACKGROUND: Molecular interaction networks summarize complex biological processes as graphs, whose structure is informative of biological function at multiple scales. Simultaneously, omics technologies measure the variation or activity of genes, prot...

Protein Abundance Prediction Through Machine Learning Methods.

Journal of molecular biology
Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing...

Fast identification of off-target liabilities in early antibiotic discovery with Fourier-transform infrared spectroscopy.

Biotechnology and bioengineering
Structural modifications of known antibiotic scaffolds have kept the upper hand on resistance, but we are on the verge of not having antibiotics for many common infections. Mechanism-based discovery assays reveal novelty, exclude off-target liabiliti...

Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods.

Nature communications
Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the seq...

Active and machine learning-based approaches to rapidly enhance microbial chemical production.

Metabolic engineering
In order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic mode...