PhageAI

PhageAI classifies bacteriophage genomes to predict lytic versus lysogenic life cycles for identification of phages suitable for therapeutic applications.

Key Features:

• Extensive Database Access: Includes access to over 10,000 publicly available bacteriophage genomes for analysis and classifier training.
• Life Cycle Classification: Distinguishes lytic and lysogenic phages with reported 98.90% accuracy on a validation set and 97.18% average accuracy on a test set.
• Advanced Machine Learning Techniques: Employs nucleotide sequence embedding based on the Word2Vec model with Ship-gram enhancements and a linear Support Vector Machine optimized via 10-fold cross-validation.
• Integration of Natural Language Processing: Applies machine learning and NLP-inspired techniques to extract features from nucleotide sequences for lifecycle prediction.

Scientific Applications:

• Therapeutic Phage Selection: Identifies phages with strictly lytic life cycles to support selection of candidates for phage therapy development.
• Bacteriophage Research and Comparative Genomics: Enables lifecycle-based classification across thousands of genomes to support studies in microbiology and genomics.
• Bioinformatics Benchmarking: Provides a high-accuracy lifecycle classifier for comparative evaluation of phage classification methods.

Methodology:

Nucleotide sequences are embedded using Word2Vec with Ship-gram enhancements; a linear Support Vector Machine performs supervised classification optimized with 10-fold cross-validation on a dataset of over 10,000 publicly available bacteriophage genomes, with reported evaluation accuracies of 98.90% (validation) and 97.18% (average test).