AIMC Topic: Bacteria

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

Nature communications Sep 1, 2021
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...
Algorithms Bacteria Green Fluorescent Proteins Neural Networks, Computer
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Recent advancement in nano-optical strategies for detection of pathogenic bacteria and their metabolites in food safety.

Critical reviews in food science and nutrition Jul 20, 2021
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...
Artificial Intelligence Biosensing Techniques Bacteria Humans Nanotechnology Food Safety
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Broad-Spectrum Bactericidal Activity and Remarkable Selectivity of Main-Chain Sulfonium-Containing Polymers with Alternating Sequences.

ACS macro letters Jul 15, 2021
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...
Bacteria Anti-Bacterial Agents Methicillin-Resistant Staphylococcus aureus Microbial Sensitivity Tests Polymers
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Microbiome Preprocessing Machine Learning Pipeline.

Frontiers in immunology Jun 18, 2021
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 ...
Mice Bacteria Humans Progesterone Neural Networks, Computer Animals Interleukin-1alpha Pregnancy Machine Learning Phylogeny Colitis Gastrointestinal Microbiome Female Mucositis Adult RNA, Ribosomal, 16S Hematopoietic Stem Cell Transplantation
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Nonlinear machine learning pattern recognition and bacteria-metabolite multilayer network analysis of perturbed gastric microbiome.

Nature communications Mar 26, 2021
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...
Stomach Helicobacter pylori Microbiota Proton Pump Inhibitors Population Dynamics Helicobacter Infections Humans Bacteria Machine Learning Gastrointestinal Microbiome RNA, Ribosomal, 16S
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Expanding the drug discovery space with predicted metabolite-target interactions.

Communications biology Mar 5, 2021
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...
Transcriptome Protein Interaction Maps Bacteria Drug Discovery Gene Expression Profiling Metabolome Anti-Inflammatory Agents Gastrointestinal Agents Signal Transduction Gastrointestinal Microbiome Metabolomics Humans Machine Learning Cells, Cultured Molecular Targeted Therapy Databases, Factual Host-Pathogen Interactions Inflammatory Bowel Diseases Data Mining Ligands
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Using neural networks to mine text and predict metabolic traits for thousands of microbes.

PLoS computational biology Mar 2, 2021
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...
Fermentation Archaea Databases, Factual Phylogeny Bacteria Computational Biology Neural Networks, Computer Acetates Data Mining
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Raman spectroscopy combined with machine learning for rapid detection of food-borne pathogens at the single-cell level.

Talanta Feb 5, 2021
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...
Food Contamination Prospective Studies Machine Learning Bacteria Spectrum Analysis, Raman
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Forest and Trees: Exploring Bacterial Virulence with Genome-wide Association Studies and Machine Learning.

Trends in microbiology Jan 14, 2021
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...
Bacteria Virulence Factors Virulence Genome-Wide Association Study Genetic Variation Genomics Machine Learning Genome, Bacterial Genotype Phylogeny
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Artificial neural networks combined multi-wavelength transmission spectrum feature extraction for sensitive identification of waterborne bacteria.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 5, 2021
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...
Neural Networks, Computer Bacteria Principal Component Analysis
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