AIMC Topic: Virulence Factors
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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...
Morphology-based classification of mycobacteria-infected macrophages with convolutional neural network: reveal EsxA-induced morphologic changes indistinguishable by naked eyes.
Translational research : the journal of laboratory and clinical medicine
Jun 28, 2019
EsxA is an essential virulence factor for Mycobacterium tuberculosis (Mtb) pathogenesis as well as an important biomarker for Mtb detection. In this study, we use light microscopy and deep learning-based image analysis to classify the morphologic cha...
Molecules Autoinducer 2 and cjA and Their Impact on Gene Expression in Campylobacter jejuni.
Journal of molecular microbiology and biotechnology
Jan 29, 2019
Quorum sensing is a widespread form of cell-to-cell communication, which is based on the production of signaling molecules known as autoinducers (AIs). The first group contains highly species-specific N-acyl homoserine lactones (N-AHLs), generally kn...
Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila.
PloS one
Jan 25, 2019
Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to change their environment making the environment hospitable for the bacteria. In recent years, several ma...
Decoding virulence and resistance in Klebsiella pneumoniae: Pharmacological insights, immunological dynamics, and in silico therapeutic strategies.
Microbial pathogenesis
Aug 1, 2025
Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the leading members of ESKAPE pathogens, it plays a major role in a wide range of infections that cause ...
Accurate prediction of virulence factors using pre-train protein language model and ensemble learning.
BMC genomics
May 21, 2025
BACKGROUND: As bacterial pathogens develop increasing resistance to antibiotics, strategies targeting virulence factors (VFs) have emerged as a promising and effective approach for treating bacterial infections. Existing methods mainly relied on sequ...
Using core genome and machine learning for serovar prediction in Salmonella enterica subspecies I strains.
FEMS microbiology letters
Jan 10, 2025
This study presents a dual investigation of Salmonella enterica subspecies I, focusing on serovar prediction and core genome characteristics. We utilized two large genomic datasets (panX and NCBI Pathogen Detection) to test machine learning methods f...
Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.
Briefings in bioinformatics
May 23, 2024
High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an e...
Mechanism of assembly of type 4 filaments: everything you always wanted to know (but were afraid to ask).
Microbiology (Reading, England)
Mar 1, 2023
Type 4 filaments (T4F) are a superfamily of filamentous nanomachines - virtually ubiquitous in prokaryotes and functionally versatile - of which type 4 pili (T4P) are the defining member. T4F are polymers of type 4 pilins, assembled by conserved mult...
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...
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