AIMC Topic: Escherichia coli

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Generating functional protein variants with variational autoencoders.

PLoS computational biology
The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function relationship directly from natural sequence variation. Deep generative models trained on protein sequ...

Deep learning the collisional cross sections of the peptide universe from a million experimental values.

Nature communications
The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million dat...

Detecting operons in bacterial genomes via visual representation learning.

Scientific reports
Contiguous genes in prokaryotes are often arranged into operons. Detecting operons plays a critical role in inferring gene functionality and regulatory networks. Human experts annotate operons by visually inspecting gene neighborhoods across pileups ...

A high-throughput and machine learning resistance monitoring system to determine the point of resistance for Escherichia coli with tetracycline: Combining UV-visible spectrophotometry with principal component analysis.

Biotechnology and bioengineering
UV-visible spectroscopy (UV-Vis) is routinely used in microbiology as a tool to check the optical density (OD) pertaining to the growth stages of microbial cultures at the single wavelength of 600 nm, better known as the OD . Typically, modern UV-Vis...

Codon optimization with deep learning to enhance protein expression.

Scientific reports
Heterologous expression is the main approach for recombinant protein production ingenetic synthesis, for which codon optimization is necessary. The existing optimization methods are based on biological indexes. In this paper, we propose a novel codon...

A machine learning Automated Recommendation Tool for synthetic biology.

Nature communications
Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long develop...

A Study of the Chemistries, Growth Mechanisms, and Antibacterial Properties of Cerium- and Yttrium-Containing Nanoparticles.

ACS biomaterials science & engineering
Under the current climate, physicians prescribe antibiotics for treating bacterial infections, and such a limitation to a single class of drugs is disadvantageous since antibiotic-resistant bacteria have adapted to withstanding their stresses. Antibi...

Machine learning-driven electronic identifications of single pathogenic bacteria.

Scientific reports
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a poly...