From Data to Discovery: Best Practices for Proteomic Data Analysis

Seer’s novel approach to mass spectrometry-based proteomics can reveal layers of biological information invisible to other methods, offering the potential for transformative insights. By adopting best practices and leveraging innovative data strategies, researchers can confidently navigate large datasets and multiomic integrations, making the most of the extraordinary depth and resolution of advanced proteomics. 

In this webinar, Serafim Batzoglou (Seer) and Uros Kuzmanov (University of Toronto) will explore the power of proteomic data, offering tips, tricks, and best practices to unlock its full potential. The session will showcase real-world examples of how to effectively analyze proteomic datasets, merge them seamlessly with other omic data, and leverage Seer's tools for fast, intuitive analysis — empowering users from novice to expert. Attendees will learn how this technology can enhance discovery power in areas such as biomarker research, disease mechanisms, and multi-omics integration. 

Learning Objectives: 

• Understand the unique power of mass spec-based proteomics to reveal deep biological insights 

• Explore how integrating proteomic data with other omic datasets enriches biological research and advances multi-dimensional discovery

• Examine advanced tools and data strategies that enable rapid analysis of large, complex datasets and uncover meaningful, deep insights

Seer's Proteograph^® workflow addresses key limitations in conventional proteomics by enabling deep, reproducible profiling across the dynamic range of complex biological samples - including low-abundance proteins. By integrating nanoparticle-based sample preparation with high-throughput mass spectrometry, the platform offers a scalable solution for large cohort studies and systems biology applications. This approach opens new possibilities in biomarker discovery, drug development, and precision medicine.