ColFeatures

ColFeatures automates identification, morphological feature extraction, temporal labeling, and clustering of bacterial colonies on agar plates to classify environmental isolates and support longitudinal microbiological analyses.

Key Features:

• Automated Identification: Recognizes bacterial colonies on agar plate images to reduce variability from manual examination.
• Morphological Data Extraction: Extracts quantitative morphological characteristics from each colony for downstream analysis.
• Temporal Tracking: Generates labels for colonies to enable tracking of temporal development in longitudinal studies.
• Machine Learning Integration: Applies machine learning clustering methodologies to sort environmental isolates based on colony features.
• Performance Evaluation: Assesses clustering quality using Silhouette, Calinski-Harabasz, and Davies-Bouldin indices.

Scientific Applications:

• Standardized Colony Analysis: Provides a standardized approach for bacterial colony phenotyping and comparison.
• Complementary to Sequencing and Mass Spectrometry: Complements sequencing and mass spectrometry workflows by supplying morphological classification and pre-sorting.
• Environmental Isolate Sorting: Supports sorting and preliminary classification of environmental isolates via morphological clustering.
• Longitudinal Growth Studies: Enables temporal analysis of colony development through labeled tracking across time points.

Methodology:

ColFeatures captures images of bacterial colonies on agar plates, processes those images to extract morphological features, applies machine learning clustering algorithms to classify and sort colonies, and evaluates clustering performance using Silhouette, Calinski-Harabasz, and Davies-Bouldin indices.