AIMC Topic: Listeria monocytogenes
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Quantitative prediction of disinfectant tolerance in Listeria monocytogenes using whole genome sequencing and machine learning.
Scientific reports
Mar 26, 2025
Listeria monocytogenes is a potentially severe disease-causing bacteria mainly transmitted through food. This pathogen is of great concern for public health and the food industry in particular. Many countries have implemented thorough regulations, an...
ListPred: A predictive ML tool for virulence potential and disinfectant tolerance in Listeria monocytogenes.
Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Mar 18, 2025
Despite current surveillance and sanitation strategies, foodborne pathogens continue to threaten the food industry and public health. Whole genome sequencing (WGS) has reached an unprecedented resolution to analyse and compare pathogenic bacterial is...
NRGCNMDA: Microbe-Drug Association Prediction Based on Residual Graph Convolutional Networks and Conditional Random Fields.
Interdisciplinary sciences, computational life sciences
Jan 7, 2025
The process of discovering new drugs related to microbes through traditional biological methods is lengthy and costly. In response to these issues, a new computational model (NRGCNMDA) is proposed to predict microbe-drug associations. First, Node2vec...
Prediction of Clonal Complexes from Multilocus Variable Number Tandem Repeat Analysis Patterns Using a Machine Learning Approach.
Foodborne pathogens and disease
Jul 4, 2024
Multilocus variable number tandem repeat analysis (MLVA) is a molecular subtyping technique that remains useful for those without the resources to access whole genome sequencing for the tracking and tracing of bacterial contaminants. Unlike technique...
Machine-Learning-Assisted Aggregation-Induced Emissive Nanosilicon-Based Sensor Array for Point-of-Care Identification of Multiple Foodborne Pathogens.
Analytical chemistry
Apr 15, 2024
How timely identification and determination of pathogen species in pathogen-contaminated foods are responsible for rapid and accurate treatments for food safety accidents. Herein, we synthesize four aggregation-induced emissive nanosilicons with diff...
Enhanced detection of Listeria monocytogenes using tetraethylenepentamine-functionalized magnetic nanoparticles and LAMP-CRISPR/Cas12a-based biosensor.
Analytica chimica acta
Oct 11, 2023
BACKGROUND: Listeria monocytogenes is a pathogenic bacterium that can lead to severe illnesses, especially among vulnerable populations. Therefore, the development of rapid and sensitive detection methods is vital to prevent and manage foodborne dise...
Semiquantitative Fingerprinting Based on Pseudotargeted Metabolomics and Deep Learning for the Identification of and Its Major Serotypes.
Analytical chemistry
Apr 4, 2023
The rapid identification of pathogenic microorganism serotypes is still a bottleneck problem to be solved urgently. Compared with proteomics technology, metabolomics technology is directly related to phenotypes and has higher specificity in identifyi...
Accurate classification of Listeria species by MALDI-TOF mass spectrometry incorporating denoising autoencoder and machine learning.
Journal of microbiological methods
Nov 21, 2021
Listeria monocytogenes belongs to the category of facultative anaerobic bacteria, and is the pathogen of listeriosis, potentially lethal disease for humans. There are many similarities between L. monocytogenes and other non-pathogenic Listeria specie...
Prediction of population behavior of Listeria monocytogenes in food using machine learning and a microbial growth and survival database.
Scientific reports
May 19, 2021
In predictive microbiology, statistical models are employed to predict bacterial population behavior in food using environmental factors such as temperature, pH, and water activity. As the amount and complexity of data increase, handling all data wit...
PeptiDesCalculator: Software for computation of peptide descriptors. Definition, implementation and case studies for 9 bioactivity endpoints.
Proteins
Sep 17, 2020
We present a novel Java-based program denominated PeptiDesCalculator for computing peptide descriptors. These descriptors include: redefinitions of known protein parameters to suite the peptide domain, generalization schemes for the global descriptio...
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