The Perseus computational platform is designed to address the challenges of downstream biological analysis of high-dimensional proteomics data. It offers a comprehensive suite of statistical tools for normalization, pattern recognition, time series analysis, cross-omics comparisons, and multiple hypothesis testing. The platform includes a machine learning module for classification and validation of patient groups, as well as detection of predictive protein signatures. Central to Perseus is an interactive workflow environment that provides complete documentation of computational methods used, making it accessible to biomedical domain experts without extensive bioinformatics training. Users can extend the software through plugins, which can be shared via a plugin store. Perseus supports various data types, including expression proteomics, posttranslational modifications, and interaction proteomics, and integrates with external resources for enriched annotations. The platform also facilitates cross-omics analysis, enabling correlation between proteomics data and other omics dimensions such as mRNA levels from RNA-seq. Additionally, Perseus incorporates machine learning techniques for detecting subtle biological associations and biomarker discovery. The software is freely available, user-friendly, and continuously maintained, aiming to bridge the gap between large-scale proteomics data generation and modeling of signaling pathways and biochemical reactions.The Perseus computational platform is designed to address the challenges of downstream biological analysis of high-dimensional proteomics data. It offers a comprehensive suite of statistical tools for normalization, pattern recognition, time series analysis, cross-omics comparisons, and multiple hypothesis testing. The platform includes a machine learning module for classification and validation of patient groups, as well as detection of predictive protein signatures. Central to Perseus is an interactive workflow environment that provides complete documentation of computational methods used, making it accessible to biomedical domain experts without extensive bioinformatics training. Users can extend the software through plugins, which can be shared via a plugin store. Perseus supports various data types, including expression proteomics, posttranslational modifications, and interaction proteomics, and integrates with external resources for enriched annotations. The platform also facilitates cross-omics analysis, enabling correlation between proteomics data and other omics dimensions such as mRNA levels from RNA-seq. Additionally, Perseus incorporates machine learning techniques for detecting subtle biological associations and biomarker discovery. The software is freely available, user-friendly, and continuously maintained, aiming to bridge the gap between large-scale proteomics data generation and modeling of signaling pathways and biochemical reactions.