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Bacteria

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Support vector machine-based prediction of pore-forming toxins (PFT) using distributed representation of reduced alphabets.

Journal of bioinformatics and computational biology
Bacterial virulence can be attributed to a wide variety of factors including toxins that harm the host. Pore-forming toxins are one class of toxins that confer virulence to the bacteria and are one of the promising targets for therapeutic interventio...

Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis.

Analytical and bioanalytical chemistry
The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the ant...

Predicting bloodstream infection outcome using machine learning.

Scientific reports
Bloodstream infections (BSI) are a main cause of infectious disease morbidity and mortality worldwide. Early prediction of BSI patients at high risk of poor outcomes is important for earlier decision making and effective patient stratification. We de...

A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms.

Scientific reports
Increasing occurrence of harmful algal blooms across the land-water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective anal...

A Deep Learning-Based Method for Identification of Bacteriophage-Host Interaction.

IEEE/ACM transactions on computational biology and bioinformatics
Multi-drug resistance (MDR) has become one of the greatest threats to human health worldwide, and novel treatment methods of infections caused by MDR bacteria are urgently needed. Phage therapy is a promising alternative to solve this problem, to whi...

Raman spectroscopy-based adversarial network combined with SVM for detection of foodborne pathogenic bacteria.

Talanta
Raman spectroscopy combined with artificial intelligence algorithms have been widely explored and focused on in recent years for food safety testing. It is still a challenge to overcome the cumbersome culture process of bacteria and the need for a la...

Advances in bacterial concentration methods and their integration in portable detection platforms: A review.

Analytica chimica acta
Early detection and identification of microbial contaminants is crucial in many sectors, including clinical diagnostics, food quality control and environmental monitoring. Biosensors have recently gained attention among other bacterial detection tech...

Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome.

Scientific reports
Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bacterial 16S marker gene but have not reported the metabolic function of the gut microbiome, which may ...

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions.

Nature communications
Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitne...

Recent advancement in nano-optical strategies for detection of pathogenic bacteria and their metabolites in food safety.

Critical reviews in food science and nutrition
Pathogenic bacteria and their metabolites are the leading risk factor in food safety and are one of the major threats to human health because of the capability of triggering diseases with high morbidity and mortality. Nano-optical sensors for bacteri...