Biological data is highly complex and diverse, with multiple variables contributing to observed trends. Analysis and interpretation of these types of data require the use of appropriate tools and methods in order to harness the most out of the data and highlight significant correlations and causal links.
What do we offer?
We develop and apply a range of statistical methods tailored to each specific problem setting, that can be used for both clinical and non-clinical datasets, for both data generated by the client as well as publically available data. Our models take into account experimental/clinical design as well as all relevant biological data. We have specific expertise in combining multi-omics data with other data sources that can be seamlessly integrated into our AI-based algorithms.