Take your IPA analysis results to the next level by comparing them to your own analyses (different timepoints, treatments, cell lines, diseased and more) or from a library of over 160,000 pre-computed datasets to find similar or opposite biological signatures. Identify key genes or entities and then explore how they are expressed across normal tissues, diseases and more from over 600,000 biological samples to gain deep context.

Attendees will learn how to:

• Use and interpret the IPA Activity Plot feature to identify key genes and regulators common across datasets
• Scan across pre-computed datasets to query for any collection of genes in a network or pathway for similar or opposite gene signature using Pattern Search
• Advance insights with the IPA Analysis Match comparison feature to compare large numbers of user datasets and/or public datasets (from GEO, SRA, cancer collections and more)