ARCT

ARCT provides a bioinformatics toolkit for comparative genomics and gerontology research by integrating Perl modules and Human Ageing Genomic Resources databases (GenAge, AnAge) to analyze genes and species-level longevity and aging traits.

Key Features:

• Perl modules: A collection of Perl modules inspired by BioPerl for automating genomic data processing and analyses.
• Data-mining tools: Tools for extracting aging-related information from diverse sources and databases.
• Algorithms: Computational algorithms for comparative genomic and gene-level analyses related to aging and longevity.
• Parsers, wrappers and spiders: Components for parsing data files, programmatic access to services, and scripted data retrieval.
• Web applications: Web-based components as part of the toolkit for accessing and serving aging-related data.
• GenAge database: Curated gene database of genes associated with aging and longevity across model organisms and human candidate genes, including genes tested for association with human longevity.
• AnAge database: Database of aging and longevity records for more than 4,000 animal species, including longevity records, developmental and reproductive traits, taxonomic information, metabolic characteristics, and aging-related observations.
• Protein-protein interaction visualization: Support for visualizing protein-protein interactions to enable systems biology analyses.
• SPSS script: An SPSS script for analysis of demographic mortality data.
• Integration with HAGR: Components integrated with the Human Ageing Genomic Resources (HAGR) platform.

Scientific Applications:

• Comparative genomics of aging: Cross-species genomic comparisons using GenAge and AnAge to study aging-related genetic patterns.
• Gene-level aging studies: Identification and analysis of genes associated with aging and longevity, including candidates tested for human longevity.
• Evolutionary and comparative biology: Evolutionary analyses of lifespan and aging traits across thousands of animal species using AnAge data.
• Systems biology: Systems-level analyses incorporating protein-protein interaction visualization.
• Demographic mortality analysis: Quantitative analysis of demographic mortality data using the provided SPSS script.
• Automated data integration: Automated retrieval and integration of aging-related data via parsers, wrappers, and spiders.

Methodology:

Uses Perl modules inspired by BioPerl, data-mining tools, algorithms, parsers, wrappers, spiders, web application components, protein-protein interaction visualization, and an SPSS script for demographic mortality analysis.