Lynx web services for annotations and systems analysis of multi-gene disorders

Area of Science:

• Systems biology
• Bioinformatics
• Computational biology

Background:

• Human phenotypes and disorders are complex, involving intricate molecular mechanisms.
• Integrating diverse biomedical data is crucial for understanding these mechanisms.
• Existing platforms may lack comprehensive data integration and advanced analytical tools.

Purpose of the Study:

• To introduce Lynx, a web-based integrated systems biology platform.
• To support annotation and analysis of experimental data.
• To generate weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders.

Main Methods:

• Integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual) from public databases and curated sources (LynxKB).
• Developed tools for gene list enrichment analysis using functional annotations.
• Implemented network-based gene prioritization methods.
• Provided access to data and tools via REST-based Web Services.

Main Results:

• Lynx successfully integrates diverse biomedical data into a unified platform.
• The platform offers robust tools for gene enrichment analysis and network-based gene prioritization.
• Web services enable programmatic access to data retrieval, searching LynxKB, and analytical tools.

Conclusions:

• Lynx provides a powerful, integrated systems biology platform for researchers.
• It facilitates the generation of hypotheses regarding molecular mechanisms underlying human disorders.
• The platform's web services enhance accessibility and interoperability for data analysis.