Learn how to quickly and easily identify significant pathways, discover potential novel regulatory networks, and get the most out of your 'omics data!

IPA has broadly been adopted by the life science research community and is cited in thousands of articles for the analysis, integration, and interpretation of data derived from ‘omics experiments, such as RNA-seq, small RNA-seq, microarrays including miRNA and SNP, metabolomics, proteomics, and small scale experiments. Hosted by two QIAGEN Senior Scientists, this series will show you step-by-step how to implement and use IPA to get the most out of your data.

Part 1: Introduction to the IPA Core Analysis

Learn how to view and interpret Core Analysis results in IPA, which allows you to relate the molecules in your dataset to information in the QIAGEN Knowledge Base. You will learn how to:

• Uncover signaling and metabolic canonical pathways enriched in your data
• Predict activation or inhibition of upstream regulators
• Identify biological functions and diseases that are predicted to be increasing or decreasing
• Generate causal hypotheses
• Build networks describing potential molecular interactions of your dataset molecules
• Compare your analyses to thousands of analyses created from public datasets