AlgaePath

AlgaePath provides integrated analysis of metabolic pathways using transcript abundance data from next-generation sequencing (NGS) in green algae such as Chlamydomonas reinhardtii and Neodesmus sp. UTEX 2219-4.

Key Features:

• Integrated Database: Consolidates gene expression (transcript abundance) data with curated biological pathways for green algae.
• Pathway Visualization: Maps transcript abundance for 45 Chlamydomonas reinhardtii samples and 4 Neodesmus sp. UTEX 2219-4 samples onto detailed metabolic pathway diagrams.
• Differential Expression Analysis: Implements a Folds Search function to identify genes that are differentially expressed between two conditions.
• Pathway Enrichment and Co-expression Analysis: Provides pathway enrichment via Gene Group Analysis and identifies co-expressed transcripts via Co-expression Analysis to investigate gene sets and regulatory relationships.

Scientific Applications:

• Functional Genomics: Links transcript abundance to metabolic pathways to infer gene functions and interactions within the cellular context.
• Systems Biology: Enables systems-level analysis of metabolic networks by integrating transcriptomic data with pathway information.
• Metabolic Engineering: Supports identification of target genes and pathways for metabolic optimization in applications such as biofuel production and bioremediation.
• Environmental and Stress Response Studies: Analyzes differential gene expression across conditions to investigate responses to environmental changes or stressors.

Methodology:

Uses next-generation sequencing (NGS) transcript abundance data integrated with curated biological pathways; includes Folds Search for differential expression, Gene Group Analysis for pathway enrichment, and Co-expression Analysis for identifying co-expressed transcripts.