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Bacteria

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Broad-Spectrum Bactericidal Activity and Remarkable Selectivity of Main-Chain Sulfonium-Containing Polymers with Alternating Sequences.

ACS macro letters
Incorporation of cationic groups into polymers represents one of the most widely used strategies to prepare antibacterial materials. Sulfonium, as a typical cationic moiety, displays potent antibacterial efficacy in the form of small molecules, howev...

Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology
BACKGROUND: 16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ...

Nonlinear machine learning pattern recognition and bacteria-metabolite multilayer network analysis of perturbed gastric microbiome.

Nature communications
The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PPIs), or bacterial infection such as Helicobacter pylori, cause significant microbial alterations. Ye...

Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology
Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potenti...

Using neural networks to mine text and predict metabolic traits for thousands of microbes.

PLoS computational biology
Microbes can metabolize more chemical compounds than any other group of organisms. As a result, their metabolism is of interest to investigators across biology. Despite the interest, information on metabolism of specific microbes is hard to access. I...

Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level.

Talanta
Rapid detection of food-borne pathogens in early food contamination is a permanent topic to ensure food safety and prevent public health problems. Raman spectroscopy, a label-free, highly sensitive and dependable technology has attracted more and mor...

Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

Trends in microbiology
The advent of inexpensive and rapid sequencing technologies has allowed bacterial whole-genome sequences to be generated at an unprecedented pace. This wealth of information has revealed an unanticipated degree of strain-to-strain genetic diversity w...

Artificial neural networks combined multi-wavelength transmission spectrum feature extraction for sensitive identification of waterborne bacteria.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Present research is focused on the rapid and accurate identification of bacterial species based on artificial neural networks combined with spectral data processing technology. The spectra of different bacterial species in the logarithmic growth phas...

C-Norm: a neural approach to few-shot entity normalization.

BMC bioinformatics
BACKGROUND: Entity normalization is an important information extraction task which has gained renewed attention in the last decade, particularly in the biomedical and life science domains. In these domains, and more generally in all specialized domai...

Bacterial endosymbiont inhabiting leaves and their antioxidant and antidiabetic potential.

Journal of complementary & integrative medicine
OBJECTIVES: Research on endosymbionts is emerging globally and is considered as a potential source of bioactive phytochemicals. The present study examines the antioxidant and antidiabetic of the endophytic crude extract isolated from leaves.