Sophisticated data analysis
Machine learning is reliant upon the ability to standardise entities, a process that can be hugely time consuming and require specialist resources when carried out manually. The Aigenpulse Platform automates much of this process, matching terms in uploaded data to a standard ontology, saving time and hassle, and allowing the Analytics Module to run advanced analyses in real time.
Powerful data structures
The Aigenpulse Platform is built around a fully standardised hierarchy of biological ontologies – diseases, organs, disease sites, tissues and healthy cell types. This makes it simple to link data relating to any biological entity across all relevant ontological terms. Once linked, all of the ontological terms are standardised, which reduces any ambiguity. These terms can then be used to annotate other entities, say, patient-derived tissue samples, in the Aigenpulse Platform. This ability greatly simplifies analysis of your annotated dataset in the context of multiple disparate datasets across teams, platforms, and data providers, enhancing efficiency when interacting with large disparate datasets.
Simplify you Entity Standardisation
Click here to find out more about simplifying standardisation of entities
Flexible to suit
We understand that everyone has their own way of working, so the Aigenpulse Platform makes it easy for you to define your own aliases for particular ontological terms. Smart ontology management means that just about any custom terms can be mapped – which is great for users wanting to use their preferred terms – while maintaining the power of a full standard ontological hierarchy. This is especially important if there are many different terms being used for the same entity across different teams or collaborators.