alfaNET

alfaNET provides proteome annotations and predictive host–pathogen interaction analyses to study molecular interactions between alfalfa and Pseudomonas syringae pv. syringae ALF3.

Key Features:

• Proteome Annotations: Comprehensive annotations of the Pseudomonas syringae pv. syringae ALF3 proteome with functional assignments relevant to pathogenicity.
• Host-Pathogen Interactome Tool: Orthology-based predictions map interactions between alfalfa host proteins and bacterial effector proteins.
• Subcellular Localization Annotations: Annotations of subcellular localization for pathogen proteins to indicate likely cellular compartments of action.
• Gene Ontology (GO) Annotations: GO annotations for functional categorization and biological process analysis of proteins.
• Network Visualization: Network visualization of host–pathogen interaction networks to support identification of key molecular players.
• Effector Protein Prediction: Predictive models identify candidate effector proteins implicated in pathogenesis.
• Search and Filtering: Keyword search and protein-length filtering for targeted retrieval of proteome records.
• BLAST Homology Search: Integrated BLAST searches against both alfalfa and Pseudomonas proteomes for homology and comparative analyses.

Scientific Applications:

• Molecular Plant Pathology: Support molecular studies of alfalfa–Pseudomonas syringae pv. syringae ALF3 interactions.
• Resistance Target Identification: Facilitate identification of candidate genes and effector targets for breeding or engineering alfalfa resistance.
• Functional and Pathway Analysis: Enable functional categorization and pathway analysis of proteins involved in bacterial stem blight.
• Comparative and Evolutionary Analysis: Support comparative and evolutionary analyses of alfalfa and Pseudomonas proteomes.

Methodology:

Orthology-based predictions to infer host–pathogen interactions; proteome annotation including GO and subcellular localization annotations; predictive models for effector identification; BLAST homology searches; integration of annotations with interaction predictions and network visualization.