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Scientific challenge

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.

Key features

  • 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
  • Prioritize shortlists of candidate targets following a rational, data-driven and collaborative process
  • Justify which targets are most relevant with all the available evidence
  • Translate biological questions into a data journey that showcases existing/absent data sources
  • Adopt agile methodologies to enhance, reuse and share prioritization models, and change objectives on the fly
  • Define computationally-predicted functionality for potential targets and compound desirability

Ready to get started?

Explore the platform

services
Augment the internal data estate with an industry-defining data universe designed to accelerate collaborative innovation in the microbiome space.
low-code customer apps
Compose robust low-code applications covering a range of business needs. Extend e[datascientist] to deliver custom capabilities and experiences.

Innovating for a better future

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