Targets are often prioritized based on opinions, assumptions or previous studies. But not enough are based on real data.
A lack of standardization impedes effective target prioritization, and it is difficult to place targets within a broader data context (a network) to effectively elucidate potential intervention methods and outcomes.
Report generation is time-consuming and lacks traceability, as results are often separated from the originating data.
e[target] prioritizes targets in a collaborative, traceable and data-driven method, presented in a highly visual manner.
Rank and prioritize targets or any entity of interest (e.g. genes, proteins, chemical compounds, bacteria, etc.) using multi-criteria valuation capabilities
Continuously build and evolve prioritization models in accordance with company scientific standards, and collaborate with colleagues
Perform downstream data exploration and analysis (e.g. regression, non-linear regression, clustering, graph metrics)
Explore and evaluate target function, suitability and essentiality using an intuitive, data-driven interface
Export comprehensive reports within minutes, ensuring traceability, transparency and collaboration
Eagle Genomics’ innovative approach in establishing a platform-driven ecosystem for the generation and exchange of scientific data-derived assets is of great potential value to Unilever.
Healthy animals, healthy people and a healthy planet are all interconnected. With the advanced knowledge and insights we anticipate generating from our microbiome data, the e[datascientist] will allow us to bring more relevant products to market.
As a company driven by innovation, Reckitt collaborates with partners who bring powerful new capabilities to the table so we can deliver disruptive ideas to the market.
