Time to create robust scientific product claims through a data driven process. Whether it’s the innovation of plant-based products, analysis of animal gut health for better food, or the creation of functional foods and ingredients, the e[datascientist] is the answer.
Organisations already on board the Eagle Genomics’ train
The world is facing new challenges like never before
- Make scientific plant-based product claims
- Delve into animal biology and create nutrition rich food and feed through in-depth analysis of intestinal microbiota present in animal hosts
- Develop healthy packaged products with the right balance of micronutrients and probiotics
- Understand the role of the gut microbiome present in humans in order to address immunity issues, diabetes, obesity and more
- Analyse the relationship between health and mental wellness in humans


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"Not only our science has to evolve — also our way of doing microbiome research and understanding multi-omics. Without Eagle Genomics’ data pipelines, we would learn something from each scientific study, but it wouldn’t go anywhere beyond that." Samantha Tucker-Samaras, Global Vice President Science & Technology, Beauty and Personal Care R&D at Unilever.
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The e[exploration] collection
The e[datascientist]’s exploration collection applies a data driven approach that encompases network science and graph theory to:
- Provide a curated and catalogued data repository generated from multiple databases such as KEGG, Human Metabolite Database, FooDB etc.
- Enable scientists to infer key relationships, and the strength of those relationships, between different entities via an intuitive scoring system.
- Equip teams to normalise, standardise and correct data for further statistical analysis and graph exploration.
- Provide scientists with the ability to improve hypothesis formulation through an interactive and exploratory data analysis approach, and apply the formulated hypotheses on a broad range of datasets.
Interested in learning more? Have a look at Eagle Genomics' e[datascientist].
![e[datascientist]](https://no-cache.hubspot.com/cta/default/2869527/d4197b50-65ec-404d-9203-aefec2c86d48.png)