Bacterial Infection

Predicting Host Association for Shiga Toxin-Producing E. coli Serogroups by Machine Learning.

Escherichia coli is a species of bacteria that can be present in a wide variety of mammalian hosts and potentially soil environments. E. coli has an open genome and can show considerable diversity in gene content between isolates. It is a reasonable assumption that gene content reflects evolution of strains in particular host environments and therefore can be used to predict the host most likely t...

Antimicrobial, Cytotoxic and Oxidative Stress Inhibitory Activities of Terpenoids and Flavonols from (Oliv.) P.J.H. Hurter.

(knob thorn) is a deciduous tree distributed in savannah regions from Tanzania to South Africa used for timber but also medicinally for the treatment of convulsions, wounds, and skin problems. In this study, the biological activities of six phytocompounds, namely: 3 -hydroxy-20(29)-en-lupan-30-al (), 30-hydroxylup-20(29)-en-3 -ol (), -kaur-15-en-18,20-diol (), melanoxetin (), quercetin () and q...

Convolutional neural network-based annotation of bacterial type IV secretion system effectors with enhanced accuracy and reduced false discovery.

The type IV bacterial secretion system (SS) is reported to be one of the most ubiquitous SSs in nature and can induce serious conditions by secreting ...

Predicting bacterial virulence factors - evaluation of machine learning and negative data strategies.

Bacterial proteins dubbed virulence factors (VFs) are a highly diverse group of sequences, whose only obvious commonality is the very property of bein...

Machine Learning To Predict Serious Bacterial Infections in Young Febrile Infants.

BACKGROUND: Recent decision rules for the management of febrile infants support the identification of infants at higher risk of serious bacterial infe...

Comparative study of antibacterial activity between Schiff base nicotinic hydrazide derivative and its silver architected nanoparticles with atomic force microscopic study of bacterial cell wall.

The threat of multi-drug resistant bacterial pathogens evokes researchers to synthesized safe and effective chemotherapeutic agents for nano-drug deli...

A novel approach for remote detection of bacteria using simple charge-coupled device cameras and telescope.

We have designed, constructed, and utilized a charge-coupled device system, integrated with a small Newtonian telescope, capable of long distance reco...

Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.

Pneumonia is one of the leading causes of childhood mortality worldwide. Chest x-ray (CXR) can aid the diagnosis of pneumonia, but in the case of low ...

Enzyme-powered Janus platelet cell robots for active and targeted drug delivery.

Transforming natural cells into functional biocompatible robots capable of active movement is expected to enhance the functions of the cells and revol...

Learning transferable deep convolutional neural networks for the classification of bacterial virulence factors.

MOTIVATION: Identification of virulence factors (VFs) is critical to the elucidation of bacterial pathogenesis and prevention of related infectious di...

Machine learning predicts new anti-CRISPR proteins.

The increasing use of CRISPR-Cas9 in medicine, agriculture, and synthetic biology has accelerated the drive to discover new CRISPR-Cas inhibitors as p...

A Deep Learning Approach to Antibiotic Discovery.

Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we traine...

PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.

MOTIVATION: Gram-positive bacteria have developed secretion systems to transport proteins across their cell wall, a process that plays an important ro...

Hybrid Design of Isonicotinic Acid Hydrazide Derivatives: Machine Learning Studies, Synthesis and Biological Evaluation of their Antituberculosis Activity.

BACKGROUND: Tuberculosis (TB) is an infection disease caused by Mycobacterium tuberculosis (Mtb) bacteria. One of the main causes of mortality from TB...

Studies for Bacterystic Evaluation against of 2-Naphthoic Acid Analogues.

BACKGROUND: Staphylococcus aureus is a gram-positive spherical bacterium commonly present in nasal fossae and in the skin of healthy people; however, ...

OCCAM: prediction of small ORFs in bacterial genomes by means of a target-decoy database approach and machine learning techniques.

Small open reading frames (ORFs) have been systematically disregarded by automatic genome annotation. The difficulty in finding patterns in tiny seque...

A guide to machine learning for bacterial host attribution using genome sequence data.

With the ever-expanding number of available sequences from bacterial genomes, and the expectation that this data type will be the primary one generate...

Artificial neural network-assisted Fourier transform infrared spectroscopy for differentiation of Salmonella serogroups and its application on epidemiological tracing of Salmonella Bovismorbificans outbreak isolates from fresh sprouts.

Salmonellae represent one of the most common bacterial infection reagents in both humans and animals. For detection and epidemiological elucidation of...

Bastion3: a two-layer ensemble predictor of type III secreted effectors.

MOTIVATION: Type III secreted effectors (T3SEs) can be injected into host cell cytoplasm via type III secretion systems (T3SSs) to modulate interactio...

DeepT3: deep convolutional neural networks accurately identify Gram-negative bacterial type III secreted effectors using the N-terminal sequence.

MOTIVATION: Various bacterial pathogens can deliver their secreted substrates also called effectors through Type III secretion systems (T3SSs) into ho...