TYPE OF SUPPORT
Research Background
Ingenuity Pathway Analysis (IPA) is a powerful bioinformatics tool that enables researchers to interpret complex omics data by mapping it onto known biological pathways and networks. Its ability to integrate diverse datasets, such as gene expression, proteomics, and metabolomics, helps uncover molecular mechanisms, identify biomarkers, and predict downstream effects, significantly accelerating discoveries in biomedical research.
Bioinformatics tools like this are typically used intensively at specific stages of the research data cycle, rather than on a daily basis. This usage pattern highlights the value of the shared cost model, it ensures researchers have access to the tools they need when they need them, without the burden of paying for year-round access they may not fully utilise.
QCIF Role
QCIF has successfully negotiated with QIAGEN, a statewide shared license for IPA, significantly reducing costs for researchers across Queensland. Through this license, researchers will gain access to IPA’s proprietary Knowledge Base, a repository of expertly curated biological interactions and functional annotations created from peer-reviewed literature. This resource provides high quality, biologically insights that go beyond raw data found in public databases.
QCIF’s distinctive position as a collaborative, statewide organisation has enabled the coordination and pooling of resources across institutions. Under this license, two users can access IPA concurrently.
QCIF manages access by creating individual user accounts and overseeing a booking system to ensure fair and efficient usage.
Research Outcome & Impact
We now have 211 registered users. Over the period from August 2024 to May 2025, we have had an impressive total of 858 sessions conducted by 95 unique users, resulting in a cumulative usage of 1,159 hours.
Access to IPA and the associated support through QCIF has enabled a newfound capacity in our team to generate insightful bioinformatics analyses from our proteomics datasets. Previously, we were entirely reliant on collaborators or other, less effective software packages that were not accessible or intuitive. Such difficulties prove major obstacles for new entrants to this kind of analysis; this is resolved with access to IPA which represents an easy-to-use, powerful software. I am eager to continue using IPA to generate bioinformatics analyses for informing future hypotheses and contributing to impactful research and consequent publications within our team.
Anuk Indraratn, Institute for Biomedicine and Glycomics, Griffith University
