AIMC Topic: Bacteria
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Machine learning for microbial identification and antimicrobial susceptibility testing on MALDI-TOF mass spectra: a systematic review.
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Mar 23, 2020
BACKGROUND: The matrix assisted laser desorption/ionization and time-of-flight mass spectrometry (MALDI-TOF MS) technology has revolutionized the field of microbiology by facilitating precise and rapid species identification. Recently, machine learni...
Machine learning methods for microbiome studies.
Journal of microbiology (Seoul, Korea)
Feb 27, 2020
Researches on the microbiome have been actively conducted worldwide and the results have shown human gut bacterial environment significantly impacts on immune system, psychological conditions, cancers, obesity, and metabolic diseases. Thanks to the d...
Microbial Decolorization of Triazo Dye, Direct Blue 71: An Optimization Approach Using Response Surface Methodology (RSM) and Artificial Neural Network (ANN).
BioMed research international
Feb 18, 2020
The release of wastewater from textile dyeing industrial sectors is a huge concern with regard to pollution as the treatment of these waters is truly a challenging process. Hence, this study investigates the triazo bond Direct Blue 71 (DB71) dye deco...
Essential oils against bacterial isolates from cystic fibrosis patients by means of antimicrobial and unsupervised machine learning approaches.
Scientific reports
Feb 14, 2020
Recurrent and chronic respiratory tract infections in cystic fibrosis (CF) patients result in progressive lung damage and represent the primary cause of morbidity and mortality. Staphylococcus aureus (S. aureus) is one of the earliest bacteria in CF ...
Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes.
Microbiome
Feb 11, 2020
BACKGROUND: Microorganisms in activated sludge (AS) play key roles in the wastewater treatment processes. However, their ecological behaviors and differences from microorganisms in other environments have mainly been studied using the 16S rRNA gene t...
VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning.
PLoS computational biology
Jan 13, 2020
Antimicrobial resistance (AMR) is an increasing threat to public health. Current methods of determining AMR rely on inefficient phenotypic approaches, and there remains incomplete understanding of AMR mechanisms for many pathogen-antimicrobial combin...
UPLC-ESI-MS/MS based identification and antioxidant, antibacterial, cytotoxic activities of aqueous extracts from storey onion (Allium cepa L. var. proliferum Regel).
Food research international (Ottawa, Ont.)
Dec 30, 2019
Storey onion (Allium cepa L. var. proliferum Regel) is a variety of onion commonly grown in northern China that has not been researched in detail. This study aimed to identify the chemical compositions of storey onion aqueous extracts by UPLC-ESI-MS/...
iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou's 5-Steps Rule and Informative Physicochemical Properties.
International journal of molecular sciences
Dec 20, 2019
Understanding of quorum-sensing peptides (QSPs) in their functional mechanism plays an essential role in finding new opportunities to combat bacterial infections by designing drugs. With the avalanche of the newly available peptide sequences in the p...
Detecting antimicrobial peptides by exploring the mutual information of their sequences.
Journal of biomolecular structure & dynamics
Dec 18, 2019
The rise of antibiotic resistance in pathogenic bacteria is a growing concern for every part of the world. The present study shows the prediction efficiency of mutual information for the classification of antimicrobial peptides. The proven role of an...
A hybrid deep learning framework for bacterial named entity recognition with domain features.
BMC bioinformatics
Dec 2, 2019
BACKGROUND: Microbes have been shown to play a crucial role in various ecosystems. Many human diseases have been proved to be associated with bacteria, so it is essential to extract the interaction between bacteria for medical research and applicatio...
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