Finding differential expressed genes or proteins can be challenging, especially when dealing with complex research questions like identifying molecular determinants of disease relapse years ahead. In the worst case no significant hits could be found at all. But fear not, there’s a solution: utilize Network Enrichment Analysis (NEA) to uncover pathways associated with your phenotype of interest. Unlike traditional methods, NEA is highly sensitive and specific, detecting compact, functionally relevant signaling and regulatory events.
NEA has proven invaluable in a number of studies, such as demonstrating drug activity, identifying drug resistance signatures, and pinpointing cytokines specific to autoimmune pathologies. Interested in learning more about NEA and its applications? Check out the success stories by the links below:
– NEA in anti-cancer drug activity by Sprint Bioscience.
– NEA in drug resistance signatures by Karolinska Institutet.
– NEA in key cytokine discovery for autoimmune pathologies by Umeå University.
The possibilities with NEA and other methods are vast. Reach out to explore more efficient tools and resources for your research endeavors.