Align-paths

Align-paths infers pathway decomposition across multiple species by clustering genes to identify core genes within metabolic pathways using KEGG genomic data and user-defined genome selections.

Key Features:

• Pathway Decomposition: Deconstructs metabolic pathways to identify core genes that play pivotal roles within those pathways.
• Gene Clustering (MCL): Uses the Markov Cluster Algorithm (MCL) to detect clusters of related genes based on functional and phylogenetic associations.
• Multi-layer Gene Analysis: Discerns distinct layers of gene involvement at both phylogenetic and functional levels within pathways.
• Cross-Species Analysis: Performs comparative pathway analysis across multiple species to identify conserved genetic functions and evolutionary patterns.
• KEGG Integration and Genome Selection: Extracts genomic and pathway data from the KEGG database and accepts user-defined genome selections as input.
• Experimental Evaluation: Demonstrated robustness through experimental evaluation in three characteristic case studies.

Scientific Applications:

• Functional Genomics: Identifying core pathway genes to elucidate gene functions in diverse biological contexts.
• Evolutionary Biology: Analyzing gene clusters at the phylogenetic level to study conservation and divergence of metabolic pathways.
• Systems Biology: Informing models of cellular processes by revealing gene contributions to pathway dynamics across species.

Methodology:

Extracts genomic and pathway data from KEGG, applies the MCL clustering algorithm to detect gene clusters representing distinct layers of pathway involvement, and evaluates results via three characteristic case studies.