AIMC Topic: Bacteria
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Enhancing robustness and generalization in microbiological few-shot detection through synthetic data generation and contrastive learning.
Computers in biology and medicine
Jun 1, 2025
In many medical and pharmaceutical processes, continuous hygiene monitoring is crucial, often involving the manual detection of microorganisms in agar dishes by qualified personnel. Although deep learning methods hold promise for automating this task...
Paving the way for bacteria-based drug delivery: biohybrid microrobots emerging from microrobotics and synthetic biology.
Advanced drug delivery reviews
Jun 1, 2025
Advances in microrobotics and synthetic biology are paving the way for innovative solutions to long-standing challenges in drug delivery. Both fields have independently worked on engineering bacteria as a therapeutic system, focusing on enhancing pro...
RABiTPy: an open-source Python software for rapid, AI-powered bacterial tracking and analysis.
BMC bioinformatics
May 18, 2025
Bacterial tracking is crucial for understanding the mechanisms governing motility, chemotaxis, cell division, biofilm formation, and pathogenesis. Although modern microscopy and computing have enabled the collection of large datasets, many existing t...
Deep learning enabled open-set bacteria recognition using surface-enhanced Raman spectroscopy.
Biosensors & bioelectronics
May 15, 2025
Accurate bacterial identification is vital in medical and healthcare settings. Traditional methods, though reliable, are often time-consuming, underscoring the need for faster, more efficient alternatives. Deep learning-assisted Surface-enhanced Rama...
Innovative fast and low-cost method for the detection of living bacteria based on trajectory.
Scientific reports
May 13, 2025
Detection of pathogens is a major concern in many fields like medicine, pharmaceuticals, or agri-food. Most conventional detection methods require skilled staff and specific laboratory equipment for sample collection and analysis or are specific to a...
Impact of Blastocystis carriage and colonization intensity on gut microbiota composition in a non-westernized rural population from Colombia.
PLoS neglected tropical diseases
May 1, 2025
BACKGROUND: The role of Blastocystis, a common intestinal parasitic protist of humans and other animals, in human health and disease remains elusive. Recent studies suggest a connection between Blastocystis colonization, healthier lifestyles, and hig...
Negative dataset selection impacts machine learning-based predictors for multiple bacterial species promoters.
Bioinformatics (Oxford, England)
Mar 29, 2025
MOTIVATION: Advances in bacterial promoter predictors based on machine learning have greatly improved identification metrics. However, existing models overlooked the impact of negative datasets, previously identified in GC-content discrepancies betwe...
PharaCon: a new framework for identifying bacteriophages via conditional representation learning.
Bioinformatics (Oxford, England)
Mar 4, 2025
MOTIVATION: Identifying bacteriophages (phages) within metagenomic sequences is essential for understanding microbial community dynamics. Transformer-based foundation models have been successfully employed to address various biological challenges. Ho...
MOSTPLAS: a self-correction multi-label learning model for plasmid host range prediction.
Bioinformatics (Oxford, England)
Mar 4, 2025
MOTIVATION: Plasmids play an essential role in horizontal gene transfer, aiding their host bacteria in acquiring beneficial traits like antibiotic and metal resistance. There exist some plasmids that can transfer, replicate, or persist in multiple or...
Using gut microbiome metagenomic hypervariable features for diabetes screening and typing through supervised machine learning.
Microbial genomics
Mar 1, 2025
Diabetes mellitus is a complex metabolic disorder and one of the fastest-growing global public health concerns. The gut microbiota is implicated in the pathophysiology of various diseases, including diabetes. This study utilized 16S rRNA metagenomic ...
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