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Bacteria

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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 ...

Electrochemical inhibition bacterial sensor array for detection of water pollutants: artificial neural network (ANN) approach.

Analytical and bioanalytical chemistry
This work reports on further development of an inhibition electrochemical sensor array based on immobilized bacteria for the preliminary detection of a wide range of organic and inorganic pollutants, such as heavy metal salts (HgCl, PbCl, CdCl), pest...

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...

Learning Single-Cell Distances from Cytometry Data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric, a function that quantif...

Coupling growth kinetics modeling with machine learning reveals microbial immigration impacts and identifies key environmental parameters in a biological wastewater treatment process.

Microbiome
BACKGROUND: Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activ...

Heterologous Machine Learning for the Identification of Antimicrobial Activity in Human-Targeted Drugs.

Molecules (Basel, Switzerland)
The emergence of microbes resistant to common antibiotics represent a current treat to human health. It has been recently recognized that non-antibiotic labeled drugs may promote antibiotic-resistance mechanisms in the human microbiome by presenting ...

Incorporating microbial community data with machine learning techniques to predict feed substrates in microbial fuel cells.

Biosensors & bioelectronics
The complicated interactions that occur in mixed-species biotechnologies, including biosensors, hinder chemical detection specificity. This lack of specificity limits applications in which biosensors may be deployed, such as those where an unknown fe...

Whey Protein Complexes with Green Tea Polyphenols: Antimicrobial, Osteoblast-Stimulatory, and Antioxidant Activities.

Cells, tissues, organs
Polyphenols are known for their antimicrobial activity, whilst both polyphenols and the globular protein β-lactoglobulin (bLG) are suggested to have antioxidant properties and promote cell proliferation. These are potentially useful properties for a ...

Metabarcoding and machine learning analysis of environmental DNA in ballast water arriving to hub ports.

Environment international
While ballast water has long been linked to the global transport of invasive species, little is known about its microbiome. Herein, we used 16S rRNA gene sequencing and metabarcoding to perform the most comprehensive microbiological survey of ballast...

Albumin binding, anticancer and antibacterial properties of synthesized zero valent iron nanoparticles.

International journal of nanomedicine
BACKGROUND: Nanoparticles (NPs) have been emerging as potential players in modern medicine with clinical applications ranging from therapeutic purposes to antimicrobial agents. However, before applications in medical agents, some in vitro studies sho...