The document discusses modeling biological systems through integrating cross-species data. It presents several methods for data integration, including analyzing genomic neighborhood, species co-occurrence, gene fusions, literature co-mentioning, and experimental interaction data. It stresses that quality control is crucial for large-scale data integration to improve data quality through scoring, benchmarking, and filtering. Integrating data across multiple species and automated literature mining can generate novel biological discoveries and highly specific hypotheses about protein networks.