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Bacteria

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Label-free deep learning-based species classification of bacteria imaged by phase-contrast microscopy.

PLoS computational biology
Reliable detection and classification of bacteria and other pathogens in the human body, animals, food, and water is crucial for improving and safeguarding public health. For instance, identifying the species and its antibiotic susceptibility is vita...

Temporal Convolutional Network-Based Signal Detection for Magnetotactic Bacteria Communication System.

IEEE transactions on nanobioscience
Molecular communication (MC) aims to use signaling molecules as information carriers to achieve communication between biological entities. However, MC systems severely suffer from inter symbol interference (ISI) and external noise, making it virtuall...

Saline wastewater treatment by bioelectrochemical process (BEC) based on Al-electrocoagulation and halophilic bacteria: optimization using ANN with new approach.

Environmental technology
In the present study, a bioelectrochemical reactor (BEC) was utilized to treat two types of real saline produced water (PW). BEC was designed based on the combination of electrocoagulation (EC) process with halophilic microorganisms, and it was asses...

Modeling of astaxanthin biosynthesis via machine learning, mathematical and metabolic network modeling.

Critical reviews in biotechnology
Natural astaxanthin is synthesized by diverse organisms including: bacteria, fungi, microalgae, and plants involving complex cellular processes, which depend on numerous interrelated parameters. Nonetheless, existing knowledge regarding astaxanthin b...

Annotated dataset for deep-learning-based bacterial colony detection.

Scientific data
Quantifying bacteria per unit mass or volume is a common task in various fields of microbiology (e.g., infectiology and food hygiene). Most bacteria can be grown on culture media. The unicellular bacteria reproduce by dividing into two cells, which i...

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...

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification.

ACS applied materials & interfaces
Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional cu...

Development of prediction software to describe total mesophilic bacteria in spinach using a machine learning-based regression approach.

Food science and technology international = Ciencia y tecnologia de los alimentos internacional
The purpose of this study was to create a tool for predicting the growth of total mesophilic bacteria in spinach using machine learning-based regression models such as support vector regression, decision tree regression, and Gaussian process regressi...

Single-cell segmentation in bacterial biofilms with an optimized deep learning method enables tracking of cell lineages and measurements of growth rates.

Molecular microbiology
Bacteria often grow into matrix-encased three-dimensional (3D) biofilm communities, which can be imaged at cellular resolution using confocal microscopy. From these 3D images, measurements of single-cell properties with high spatiotemporal resolution...

Neural network based integration of assays to assess pathogenic potential.

Scientific reports
Limited data significantly hinders our capability of biothreat assessment of novel bacterial strains. Integration of data from additional sources that can provide context about the strain can address this challenge. Datasets from different sources, h...