From data to discovery: A guided approach to proteomics analysis
Proteomic data holds enormous potential—but only when it’s prepared and analyzed in the right way. This webinar series is designed to provide a clear, practical roadmap for turning proteomic data into meaningful biological insight.
Across six sessions, we’ll walk through the essential steps: preparing data through harmonization, understanding what questions proteomics can answer, and applying common downstream approaches including univariate analysis, pathway analysis, machine learning, multiomics integration, and study design.
Whether you’re new to proteomics or looking to make better use of existing data, this series will deliver a clear, practical understanding of how proteomics can fit into your research—and what steps to take to move forward with confidence.
Speakers:
David Astling,
PhD
Tala Khosroheidari,
PhD
WEBINAR 01
More than the sum of its parts: How harmonized proteomic data reveals meaning across disparate clinical cohorts
In high‑throughput proteomics, data generated across different instruments, workflows, and cohorts can remain difficult to compare even after normalization. Harmonization addresses these study‑specific differences, enabling datasets to align and reveal meaningful biological signals. The Global Neurodegeneration Proteomics Consortium (GNPC) illustrates this power by integrating 40,000 samples from 20 international groups to uncover insights not visible in isolated studies. In this webinar, you’ll learn when normalization falls short and how harmonization strengthens cross‑study and longitudinal analyses.
Learning objectives:
- Recognize when basic normalization is insufficient for comparing across studies
- Understand how harmonization aligns datasets across plates, batches, studies and time
- See how aligned datasets reveal biological signals that remain hidden after normalization alone
- Decide when harmonization strengthens longitudinal and multi-cohort analyses –and when to use alternative approaches
Speakers:
Eshita Mutt,
PhD
David Astling,
PhD
WEBINAR 02
Finding the signal: Identifying reproducible biomarkers in high-plex proteomics
Date: June 2, 2026 | Time: 11:00 AM ET
In high‑plex proteomics, the challenge is not generating data but distinguishing true biological signal from technical variability. This webinar introduces univariate analysis as a practical starting point for biomarker discovery, covering key steps such as understanding dataset structure, identifying outliers, and assessing data performance. Using harmonized datasets, we will show how univariate methods support the identification of differentially abundant proteins and establish a reliable foundation for downstream analyses.
- Recognize sources of technical variability that obscure biological signal in high‑plex proteomics
- Understand how univariate analysis supports initial QC, outlier detection, and dataset assessment.
- See how harmonized data enables identification of differentially abundant proteins.
- Establish a reliable foundation for downstream biomarker discovery and follow‑up analyses.
WEBINAR 03
Beyond the trees: See the bigger biological picture with pathway enrichment analysis
WEBINAR 04
Opening the black box: Building and evaluating machine learning models for proteomics
WEBINAR 05
Bridging different siloed data: Advancing discovery with integrated multiomics
WEBINAR 06