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Bacterial Proteins

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Morphology-based classification of mycobacteria-infected macrophages with convolutional neural network: reveal EsxA-induced morphologic changes indistinguishable by naked eyes.

Translational research : the journal of laboratory and clinical medicine
EsxA is an essential virulence factor for Mycobacterium tuberculosis (Mtb) pathogenesis as well as an important biomarker for Mtb detection. In this study, we use light microscopy and deep learning-based image analysis to classify the morphologic cha...

A Deep Learning-Based Automatic Mosquito Sensing and Control System for Urban Mosquito Habitats.

Sensors (Basel, Switzerland)
Mosquito control is important as mosquitoes are extremely harmful pests that spread various infectious diseases. In this research, we present the preliminary results of an automated system that detects the presence of mosquitoes via image processing ...

Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima.

ACS synthetic biology
Enzymes that catalyze chemical reactions at high temperatures are used for industrial biocatalysis, applications in molecular biology, and as highly evolvable starting points for protein engineering. The optimal growth temperature (OGT) of organisms ...

Soft-sensing method based on FDLS-SVM in marine alkaline protease fermentation process.

Preparative biochemistry & biotechnology
To overcome the problem that soft-sensing model cannot be updated with the bioprocess changes, this article proposed a soft-sensing modeling method which combined fuzzy c-means clustering (FCM) algorithm with least squares support vector machine theo...

DEEPred: Automated Protein Function Prediction with Multi-task Feed-forward Deep Neural Networks.

Scientific reports
Automated protein function prediction is critical for the annotation of uncharacterized protein sequences, where accurate prediction methods are still required. Recently, deep learning based methods have outperformed conventional algorithms in comput...

Machine-Learning-Based Predictor of Human-Bacteria Protein-Protein Interactions by Incorporating Comprehensive Host-Network Properties.

Journal of proteome research
The large-scale identification of protein-protein interactions (PPIs) between humans and bacteria remains a crucial step in systematically understanding the underlying molecular mechanisms of bacterial infection. Computational prediction approaches a...

Unsupervised Learning Approach for Comparing Multiple Transposon Insertion Sequencing Studies.

mSphere
Transposon insertion sequencing (TIS) is a widely used technique for conducting genome-scale forward genetic screens in bacteria. However, few methods enable comparison of TIS data across multiple replicates of a screen or across independent screens,...

SignalP 5.0 improves signal peptide predictions using deep neural networks.

Nature biotechnology
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish ...

Molecules Autoinducer 2 and cjA and Their Impact on Gene Expression in Campylobacter jejuni.

Journal of molecular microbiology and biotechnology
Quorum sensing is a widespread form of cell-to-cell communication, which is based on the production of signaling molecules known as autoinducers (AIs). The first group contains highly species-specific N-acyl homoserine lactones (N-AHLs), generally kn...

Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila.

PloS one
Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to change their environment making the environment hospitable for the bacteria. In recent years, several ma...