AIMC Topic: Bacteria
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Deep Learning Approach for Classifying Bacteria types using Morphology of Bacterial Colony.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
The significant bottlenecks in determining bacterial species are much more time-consuming and the biology specialist's long-term experience requirements. Specifically, it takes more than half a day to cultivate a bacterium, and then a skilled microbi...
Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning.
Gut microbes
Jan 1, 2022
The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make full use of the metagenomics data of the gut microbiome to determine the age of the host. In this stu...
A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains.
Briefings in bioinformatics
Nov 5, 2021
Recently, the frequency of observing bacterial strains without known genetic components underlying phenotypic resistance to antibiotics has increased. There are several strains of bacteria lacking known resistance genes; however, they demonstrate res...
Deep Learning Assisted Microfluidic Impedance Flow Cytometry for Label-free Foodborne Bacteria Analysis and Classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
According to the urgent need for rapid detection and identification of foodborne bacteria to prevent public health event, a microfluidic electrical impedance flow cytometry assisted with convolutional neural network (ConvNet) based deep learning algo...
A NLP Pipeline for the Automatic Extraction of Microorganisms Names from Microbiological Notes.
Studies in health technology and informatics
Oct 27, 2021
According to the "Istituto Superiore di Sanita'" (ISS), hospital infections are the most frequent and serious complication of health care. This constitutes a real health emergency which requires incisive and joint action at all levels of the local an...
Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.
Briefings in bioinformatics
Sep 2, 2021
Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a crucial role in a myriad of biological processes and cellular functions. AMP-related studies have become increasingly popular in recent years due to antimicrobial r...
Prediction of prokaryotic transposases from protein features with machine learning approaches.
Microbial genomics
Jul 1, 2021
Identification of prokaryotic transposases (Tnps) not only gives insight into the spread of antibiotic resistance and virulence but the process of DNA movement. This study aimed to develop a classifier for predicting Tnps in bacteria and archaea usin...
DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.
Briefings in bioinformatics
May 20, 2021
Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, and the growing mass of bacterial genome sequence data provides an opportunity for computational met...
Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.
Annals of clinical and laboratory science
May 1, 2021
OBJECTIVE: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. Bacteremia with procalcitonin levels lower than 2.0 ng/mL has not received much attention, and relevant prediction models are lacking. Herein, a panel...
Predicting bacterial virulence factors - evaluation of machine learning and negative data strategies.
Briefings in bioinformatics
Sep 25, 2020
Bacterial proteins dubbed virulence factors (VFs) are a highly diverse group of sequences, whose only obvious commonality is the very property of being, more or less directly, involved in virulence. It is therefore tempting to speculate whether their...
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