Zisland Explorer

Zisland Explorer predicts genomic islands in bacterial and archaeal genomes by integrating segmental cumulative GC profile analysis to identify alien DNA fragments associated with symbiosis and pathogenesis.

Key Features:

• Segmental cumulative GC profile integration: Uses the segmental cumulative GC profile to locate candidate genomic islands based on GC content patterns.
• Homogeneity measurement: Quantifies compositional consistency within each predicted island to ensure internal uniformity.
• Heterogeneity measurement: Assesses compositional bias between a predicted island and the core genome to identify foreign origin.
• Target organisms: Applicable to bacterial and archaeal genomes for detection of alien DNA fragments.
• Improved true-positive rate: Achieves a true-positive rate (TPR) at least 10.3% higher than four other genomic island prediction tools.
• Balanced evaluation and experimental validation: Maintains overall accuracy with improved equilibrium among evaluation indexes and shows increased accuracy on experimental island data.

Scientific Applications:

• Microbial genomics: Investigation of genome evolution, pathogenesis, and symbiotic relationships through identification of genomic islands.
• Horizontal gene transfer analysis: Detection and characterization of acquisition and integration of foreign DNA in microorganisms.
• Method benchmarking: Comparative evaluation of genomic island prediction methods using performance metrics such as TPR against four other tools.

Methodology:

Computational analysis of GC content variations using the segmental cumulative GC profile and explicit measurements of homogeneity and heterogeneity to distinguish native and foreign DNA segments.