INCA

INCA analyzes synonymous codon usage across genomes to compute codon frequencies, calculate codon usage indices (Codon Bias Index — CBI, effective number of codons — Nc, Codon Adaptation Index — CAI), and cluster genes using self-organizing maps to inform studies of gene expression regulation, protein synthesis efficiency, and evolutionary codon bias.

Key Features:

• Codon frequency computation: Calculates codon frequencies across genes and genomes.
• Usage indices calculation: Computes Codon Bias Index (CBI), Effective Number of Codons (Nc), and Codon Adaptation Index (CAI).
• Interactive graphical display: Provides interactive graphical visualization options for calculated codon usage metrics.
• Gene clustering with self-organizing maps (SOM): Clusters genes based on codon usage preferences using the self-organizing map algorithm.

Scientific Applications:

• Gene expression regulation analysis: Uses codon usage metrics and clustering to investigate mechanisms influencing gene expression levels.
• Protein synthesis efficiency studies: Assesses relationships between codon usage and translation efficiency or protein production.
• Evolutionary codon bias exploration: Examines adaptive and evolutionary patterns of synonymous codon usage across genomes.

Methodology:

Computational steps explicitly include calculation of codon frequencies, computation of CBI, Nc and CAI, interactive visualization of calculated metrics, and gene clustering via the self-organizing map algorithm.